From vtcs1::in% Tue May 27 06:41:55 1986 Date: Tue, 27 May 86 06:41:49 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #128 Status: R AIList Digest Tuesday, 27 May 1986 Volume 4 : Issue 128 Today's Topics: Seminars - Intelligent Systems on Multiprocessors (CMU) & Information Retrieval by Text Skimming (CMU) & Theory of Nested Transactions (CMU) & Intuitionist Logic & Constructive Type Theory (MIT) & Learning to Construct Abstractions (MIT) & Non-monotonicity in Probabilistic Logic (SU) & Autoepistemic Logic, Stratified Programs, Circumscription (SU) & Sequentialising Logic Programs (SU) ---------------------------------------------------------------------- Date: 13 May 1986 1533-EDT From: Theona Stefanis@A.CS.CMU.EDU Subject: Seminar - Intelligent Systems on Multiprocessors (CMU) PS SEMINAR Name: R. Bisiani, CMU Date: Monday, 19 May Time: 3:30 Place: WeH 5409 DEVELOPING INTELLIGENT SYSTEMS ON MULTIPROCESSOR ARCHITECTURES Our long-term goal is to develop a software environment that meets the need of application specialists to build and evaluate heterogeneous AI applications quickly and efficiently. Speech and vision systems are typical of this kind of AI applications. In these systems, @i(knowledge-intensive) and conventional programming techniques must be integrated while observing real time constraints and preserving good programmability characteristics. State-of-the-art AI environments solve some but not all of the problems raised by the systems we are interested in. Therefore, we are developing a set of tools, methodologies and architectures called Agora that can be used to implement custom programming environments. Agora can be customized to support the programming model that is more suitable for a given application. Agora has been designed explicitly to support multiple languages and highly parallel computations. Systems built with Agora can be executed on a number of general purpose and custom multiprocessor architectures. ------------------------------ Date: 19 May 86 15:18:26 EDT From: Michael.Mauldin@cad.cs.cmu.edu Subject: Seminar - Information Retrieval by Text Skimming (CMU) What: Thesis Proposal: Information Retrieval By Text Skimming Who: Michael L. Mauldin (MLM@CAD) When: May 29, 1986 At 3pm Where: In Wean Hall 5409 Most information retrieval systems today are word based. But simple word searches and frequency distributions do not provide these systems with an understanding of their texts. Full natural language parsers are capable of deep understanding within limited domains, but are too brittle and slow for general information retrieval. The proposed dissertation attempts to bridge this gap by using a text skimming parser as the basis for an information retrieval system that partially understands the texts stored in it. The objective is to develop a system capable of retrieving a significantly greater fraction of relevant documents than is possible with a keyword based approach, without retrieving a larger fraction of irrelevant documents. As part of my dissertation, I will implement a full-text information retrieval system called FERRET (Flexible Expert Retrieval of Relevant English Texts). FERRET will provide information retrieval for the UseNet News system, a collection of 247 news groups covering a wide variety of topics. Initially FERRET will cover NET.ASTRO, the Astronomy news group, and part of my investigation will be to demonstrate the addition of new domains with only minimal hand coding of domain knowledge. FERRET will acquire the details of a domain automatically using a script learning component. FERRET will consist of a text skimming parser (based on DeJong's FRUMP program), a case frame matcher that compares the parse of the user's query with the parses of each text stored in the retrieval system, and a user interface. The parser relies on two knowledge sources for its operation: the sketchy script database, which encodes domain knowledge, and the lexicon. The lexicon from FRUMP will be extended both by hand and automatically with syntax and synonym information from an on-line English dictionary. The script database from FRUMP will be extended both by hand and automatically by a learning component that generates new scripts based on texts that have been parsed. The learning component will evaluate the new scripts using feedback from the user, and retain the best performers for future use. The resulting information retrieval system will be evaluated by determining its performance on queries of the UseNet database, both in terms of relevant texts not retrieved and irrelevant texts that are retrieved. Over six million characters appear on UseNet each week, so there should be enough data to study performance on a large database. The main contribution of the work will be a demonstration that a text skimming retrieval system can make distinctions based on semantic roles and information that word based systems cannot make. The script learning and dictionary access are new capabilities that will be widely useful in other natural language applications. ------------------------------ Date: 19 May 1986 1619-EDT From: Theona Stefanis@A.CS.CMU.EDU Subject: Seminar - Theory of Nested Transactions (CMU) PS SEMINAR Date: Thursday, 22 May Time: 3:30 Place: WeH 7220 Prolegomenon to the Theory of Nested Transactions Michael Merritt A. T. and T. Bell Laboratories Murray Hill, New Jersey "The possibility of a thing can never be proved merely from the fact that its concept is not self-contradictory, but only through its being supported by some corresponding intuition." Immanuel Kant This talk develops the foundation for a general theory of nested transactions. Not without trepidation, it presents yet another formal model for studying concurrency and resiliency in a nested environment. This model has distinct advantages over the many alternatives, the greatest of which is the unification of a subject replete with formalisms, correctness conditions and proof techniques. The speaker is presently engaged in an ambitious project to recast the substantial amount of work in nested transactions within this single intuitive framework. The talk focuses on preliminary results of that project--a description of the model, and its use in stating and proving correctness conditions of a lock-based concurrent scheduler. This is joint work with Nancy Lynch, of the Massachusetts Institute of Technology. ------------------------------ Date: Fri 9 May 86 09:49:15-EDT From: Susan Hardy Subject: Seminar - Intuitionist Logic & Constructive Type Theory (MIT) Friday, May 9, l986 TALK 1: 10:00 a.m., TALK 2: 2:00 p.m. 2nd Floor Lounge David Turner University of Kent at Canterbury, England TALK 1: Intuitionist Logic and Functional Programming Intuitionism is a heretical school of mathematics founded by L. E. J. Brouwer in l907. The most outstanding characteristic of intuitionists is that they reject the use of Boolean logic. Recent discoveries have shown that there is deep underlying connection between intuitionist logic and functional programming. This discovery is likely to have profound consequences for the future of both subjects. The talk will attempt to explain from the beginning what intuitionist logic is about and how the coincidence with functional programming arises. TALK 2: Constructive Type Theory as a Programming Language Constructive type theory is a formal logic and set theory which has been developed by Per Martin-Lof as a foundation for constructive (or intuitionist) mathematics. Curiously, it can also be read as a (strongly typed) functional programming language, with a number of unusual properties, including that all well typed programs terminate. The talk will give an overview of the main ideas in constructive type theory from the point of view of someone trying to use it as a programming language. HOST: Professors Arvind and Rishiyur S. Nikhil ------------------------------ Date: Wed, 14 May 1986 11:16 EDT From: JHC%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU Subject: Seminar - Learning to Construct Abstractions (MIT) -- AI Revolving Seminar -- LEARNING TO CONSTRUCT ABSTRACTIONS Rick Lathrop MIT AI Lab One useful trait of an intelligent agent is to construct higher-level abstractions from a mass of detailed low-level information. This talk will explore one way an agent might be taught how to construct such abstractions, and why it might be a useful or interesting for an agent to do so. A main motivation is the possibility of the use of these abstractions to see similarities (between situations) that are obscured by the mass of irrelevant details at the lower level. Preliminary examples from the Rieger (causal) mechanism world, VLSI circuit analysis, and protein structure analysis will be discussed. Thursday, May 15, 4pm NE-43, 8th floor playroom ------------------------------ Date: 13 May 86 1511 PDT From: Vladimir Lifschitz Subject: Seminar - Non-monotonicity in Probabilistic Logic (SU) NON-MONOTONICITY IN PROBABILISTIC LOGIC Benjamin Grosof Computer Science Department, Stanford University Thursday, May 15, 4pm MJH 252 I will discuss how to formalize the notion of non-monotonicity in probabilistic reasoning, using the framework of Probabilistic Logic (cf. Nils Nilsson). I will give some motivating examples of types of non-monotonic probabilistic reasoning that seem to be found in practice. There seems to be a relationship to default inheritance, i.e. prioritized defaults of the type used in classic example of whether birds and ostriches fly. Next, I introduce the idea of maximizing conditional independence, which can be thought of as maximizing irrelevance. This can be described more simply in terms of non-monotonic reasoning on Graphoids (cf. Judea Pearl). I conjecture that an important type of non-monotonicity in probabilistic reasoning may be concisely expressed in terms of conditional independence and Graphoids. Finally, I pose as an open question how to formulate in the above terms the non-monotonic behavior of maximizing entropy, a widely-used technique in probabilistic reasoning. ------------------------------ Date: 19 May 86 1322 PDT From: Vladimir Lifschitz Subject: Seminar - Autoepistemic Logic, Stratified Programs, Circumscription (SU) AUTOEPISTEMIC LOGIC, STRATIFIED PROGRAMS AND CIRCUMSCRIPTION Michael Gelfond and Halina Przymusinska University of Texas at El Paso Thursday, May 22, 4pm MJH 252 In Moore's autoepistemic logic, a set of beliefs of a rational agent is described by a "stable expansion" of his set of premises T. If this expansion is unique then it can be viewed as the set of theorems which follow from T in autoepistemic logic. Marek gave a simple syntactic condition on T which guarantees the existence of a unique stable expansion. We will propose another sufficient condition, which is suggested by the definition of "stratified" programs in logic programming. The declarative semantics of such programs can be defined using fixed points of non-monotonic operators (Apt, Blair and Walker; Van Gelder) or by means of circumscription (Lifschitz). We show how this semantics can be interpreted in terms of autoepistemic logic. ------------------------------ Date: Fri 23 May 86 11:33:27-PDT From: Richard Treitel Subject: Seminar - Sequentialising Logic Programs (SU) PhD oral examination Tuesday June 3rd 1986 at 3 p.m. Building 200, Room 34 "Sequentialising Logic Programs" Richard Treitel In "expert systems" and other applications of logic programming, the issue arises of whether to use rules for forward or backward inference, i.e. whether deduction should be driven by the facts available to the rule or the goals that are put to it. Often some mixture of the two is cheaper than using either exclusively. I show that, under two restrictive assumptions, optimal choices of directions for the rules can be made in time polynomial in the number of rules in a recursion-free logic program. If either of these restrictions is abandoned, the optimal choice is NP-complete. I present a search algorithm for the easiest of the cases so obtained. A related issue is the ordering of the terms in a rule, which can have a strong effect on the computational cost of using the rule. Algorithms for ordering terms optimally are known, but all of them rely on the direction of inference being fixed in advance, and they apply only to a single rule considered in isolation. A more general algorithm is developed, and a way is shown to incorporate it into the choice of rule directions. This also leads to an NP-complete problem. Some attention is paid to the model of execution cost for logic programs on which these results are based. Logic programs involving recursion are not covered by this work because no satisfactory cost model exists for them. ------------------------------ End of AIList Digest ******************** From vtcs1::in% Tue May 27 06:41:43 1986 Date: Tue, 27 May 86 06:41:38 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #129 Status: R AIList Digest Tuesday, 27 May 1986 Volume 4 : Issue 129 Today's Topics: Conferences - Workshop in High Level Tools & Society for Philosophy and Psychology Annual Meeting & Principles of Database Systems & AAAI Automatic Programming Workshop ---------------------------------------------------------------------- Date: 19 May 86 16:20:51 GMT From: cbosgd!apr!osu-eddie!welch@ucbvax.berkeley.edu (Arun Welch) Subject: Conference - Workshop in High Level Tools Call for Participation WORKSHOP ON HIGH LEVEL TOOLS FOR KNOWLEDGE BASED SYSTEMS Sponsored by The American Association for Artificial Intelligence (AAAI) Laboratory for Artificial Intelligence Research The Ohio State University (OSU-LAIR) Defense Advanced Research Projects Agency (DARPA) Columbus, Ohio October 7-8, 1986 It has become increasingly clear to builders of knowledge based systems that no single representational formalism or control construct is optimal for encoding the wide variety of types of problem solving that commonly arise and are of practical significance. The structures specific to diagnosis appear ill adapted for use in design and planning tasks, and those for prediction seem unsuitable for intelligent data retrieval. Thus there appears to be a need for task-specific constructs at levels of organization above those of rules, frames, and predicate calculus, and their associated control structures. In addition to problem solving, there is a similar move for higher-level tools for knowledge acquisition and explanation. The objective of this workshop is to bring together theoreticians and builders of knowledge based systems in order to explore the prospects for tools for specifying structures at these higher levels. Presentations are invited on all aspects of high level tools for knowledge-based systems, including (but not restricted to) these topics: - The powers and limitations of existing knowledge engineering tools and techniques. - Delineating the "natural kinds" of knowledge based problem solving that can provide the basis for task specific tools. - Matching AI techniques to tasks. - Design proposals for high level knowledge engineering tools. - Integrating task-specific tools into "toolboxes" for building systems that perform complex problem solving tasks. Four copies of an extended ABSTRACT (up to 8 pages, double-spaced) should be sent to the workshop chairman before July 1, 1986. Acceptance notices will be mailed by August 1. Revised abstracts should be returned to the chairman by September 1, 1986, so that they may be bound together for distribution at the workshop. Workshop Chairman: Organizing Committee: B. Chandrasekaran, William J. Clancey, Stanford University OSU-LAIR Lee Erman, Teknowledge Inc. Richard Fikes, Intellicorp John Josephson, OSU-LAIR Allen Sears, DARPA For information and local arrangements, contact: Charlie Huff Bev Mullet (614) 422-0054 (614) 422-0248 EMail: Huff@Ohio-State.ARPA EMail: Mullet-B@Ohio-State.ARPA Huff-C@Ohio-State.CSNET {ihnp4,cbosgd}!osu-eddie!huff Department of Computer and Information Science The Ohio State University 2036 Neil Avenue Columbus, OH 43210 ------------------------------ Date: Thu, 22 May 86 00:15 EDT From: Tim Finin Subject: Conference - Society for Philosophy and Psychology Annual Meeting Forwarded From: Scott Weinstein on Wed 21 May 1986 at 6:45 Program of the SOCIETY FOR PHILOSOPHY AND PSYCHOLOGY Annual Meeting June 5 - 8, Johns Hopkins University, Baltimore, Md. THURSDAY 1-3:30 pm. TUTORIAL on Recent Work in Linguistics, Part I Syntax: D. Lightfoot; Semantics: R. Jackendoff; Phonology: A. Prince 3:40-6 pm. (Concurrent Paper Sessions) Empirical Investigations of Realism: R. McCauley, T. McKay; A. Gopnik/ L. Forguson, L. McCune Computation and Inference: C. Peacock, F. Eagen; M. Winston, L. Shelton 8-10:30 pm. SYMPOSIUM on Machine Learning: C. Glymour, S. Weinstein, T. Mitchell; S. Harnad FRIDAY 9-11:30 am. SYMPOSIUM on Inferring Normal from Pathological Function A. Caramazza, D. Caplan, T. Bever; B. von Eckardt 1-3:30 pm. TUTORIAL on Recent Work in Lingustics II: Language Acquisition: B. Landau; Neurolinguistics: E. Zuriff; Computer Processing of Natural Language: M. Liberman 3:40-6 pm. (Concurrent Paper Sessions) Perception: C. Hardin, G. Graham; P. Manfredi, J. Poland Cognitive Ethology: C. Ristau, W. Bechtel; C. Hayes; R. Millikan 8-10:30 pm. SPECIAL INVITED SESSION on Consciousness and the Bicameral Mind: Resolving the Problem of Dualism: J. Jaynes; D. Dennett, A. C. Catania SATURDAY 9-11:30 am. SYMPOSIUM on Connectionist Models and Neural Networks T. Sejnowsky, P. Smolensky, D. Lloyd; P. Churchland 1-3:15 pm. (Concurrent Paper Sessions) Emotions: R. Kraut, E. Lepore; L. Kopelman, K. Emmett Induction, Formality and the Chinese Room: P. Thagard, J. Bender; R. Double, R. Elugardo 3:25-5:45 pm. SYMPOSIUM on Self Deception: R. Audi, K. Gergen, G. Rey; P. McLaughlin 8:30 pm. Presidential Address: F. Dretske SUNDAY 9-11:30 am. SYMPOSIUM on Intentionality and Information Theory K. Sayre, D. Perlis, B. Loewer; R. van Gulick ********************************************************************** REGISTRATION: G. Hatfield, Philosophy, Johns Hopkins U., Baltimore MD 21218 MEMBERSHIP: P. Kitcher, Philosophy, U. Minnessota, Minneapolis MN 55455 UUCP: princeton!mind!harnad ------------------------------ Date: Fri, 23 May 86 11:06:22 pdt From: Moshe Vardi Subject: Conference - Principles of Database Systems CALL FOR PAPERS Sixth ACM SIGACT-SIGMOD-SIGART Symposium on PRINCIPLES OF DATABASE SYSTEMS San Diego, California, March 23-25, 1987 The conference will cover new developments in both the theoretical and practical aspects of database and knowledge-base systems. Papers are solicited which describe original and novel research about the theory, design, specification, or implementation of database and knowledge- base systems. Some suggested, although not exclusive, topics of interest are: architecture, concurrency control, database and expert systems, database machines, data models, data structures for physical implementation, deductive databases, dependency theory, distributed systems, incomplete information, user interfaces, knowledge and data management, performance evaluation, physical and logical design, query languages, recursive rules, spatial and temporal data, statistical databases, and transaction management. You are invited to submit ten copies of a detailed abstract (not a complete paper) to the program chairman: Moshe Y. Vardi IBM Research K55/801 650 Harry Rd. San Jose, CA 95120-6099, USA (408) 927-1784 vardi@ibm.com Submissions will be evaluated on the basis of significance, originality, and overall quality. Each abstract should 1) contain enough information to enable the program committee to identify the main contribution of the work; 2) explain the importance of the work - its novelty and its practical or theoretical relevance to database and knowledge-base sys- tems; and 3) include comparisons with and references to relevant literature. Abstracts should be no longer than ten double-spaced pages. Deviations from these guidelines may affect the program committee's evaluation of the paper. The program committee consists of Umesh Dayal, Tomasz Imiel- inski, Paris Kanellakis, Hank Korth, Per-Ake Larson, Yehoshua Sagiv, Kari-Jouko Raiha, Moshe Vardi, and Mihalis Yannakakis. The deadline for submission of abstracts is October 10, 1986. Authors will be notified of acceptance or rejection by December 8, 1986 (authors who supply an electronic address might be notified earlier). The accepted papers, typed on special forms, will be due at the above address by January 9, 1987. All authors of accepted papers will be expected to sign copyright release forms. Proceedings will be distributed at the conference, and will be subsequently available for purchase through ACM. General Chairman: Local Arrangements: Ashok K. Chandra Victor Vianu IBM Research Center Dept. of Computer Science P.O.Box 218 Univ. of California Yorktown Heights, NY 10598 La Jolla, CA 92093 (914) 945-1752 (619) 452-6227 ashok%yktvmx@ibm.com vianu@sdcsvax.ucsd.edu ------------------------------ Date: Fri, 23 May 86 15:04:16 edt From: als@mitre-bedford.ARPA (Alice L. Schafer) Subject: Conference - AAAI Automatic Programming Workshop The Scientific Workshop on Automatic Programming will be held under the auspices of the AAAI conference in Philadelphia. The purpose of this workshop is to gather the active researchers in this field in order to share insights gained through implementation and experimentation. Issues to be addressed include: . What are the resistant problems in Automatic Programming? . Are there metrics for comparing the conventional software development approach to an APS? . What should, and should not, be contained in a specification? . What interaction is desired between the user and an APS? . Are there basic building blocks that typify an APS? The workshop will be held on Thursday August 14th, and will last approximately three hours. The current plan is that one and a half hours will be occupied by brief (seven minutes) presentations of current work, followed by a panel discussion with active audience participation, moderated by Tom Cheatham of Harvard. Due to the size of the available rooms, we may have to limit the audience to researchers who have experience with some aspect of the APS problem. If you wish to present your current work or be on the panel you should send us a 200-800 word abstract. The decision on who will participate will be based on these abstracts. If you wish to participate as a member of the audience instead, send us a short note containing a description of your work or references to pertinent papers you have written. If we need to limit the audience we will base our decisions on these responses. Please post a printed copy of this notice at your workplace. Organized by: Alice Schafer Richard Brown Richard Piazza (617) 271-2363 (617) 271-7559 (617) 271-2363 als@mitre-bedford.arpa rhb@mitre-bedford.arpa rlp@mitre-bedford.arpa of the Knowledge-Based Automatic Programming Project (ISFI) The MITRE Corporation Mail Stop A-045 Burlington Road Bedford, MA 01730 ------------------------------ End of AIList Digest ******************** From vtcs1::in% Wed May 28 14:30:36 1986 Date: Wed, 28 May 86 14:30:29 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #130 Status: R AIList Digest Tuesday, 27 May 1986 Volume 4 : Issue 130 Today's Topics: Query - Lenat's AM, Expert Systems - AM and CYRANO, AI Tools - VAX/VMS LISP, Games - Conway's LIFE & Int. Computer Chess Association Journal & $1,000,000 Go Prize, Humor - IT*S Grammar & Foo-Bar & Autonomous Systems ---------------------------------------------------------------------- Date: 20 May 86 14:06:59 GMT From: ihnp4!houxm!whuxl!whuxlm!akgua!gatech!itm!danny@ucbvax.berkeley.edu Subject: Need Ref for "Automated Mathematician" by Doug Lenat I read a small article in the "IEEE Expert" magazine about Doug Lenat's Doctoral dissertation at Stanford. He developed a program called "AM" (for Automated Mathematician) that produced "interesting" formulas/relationships about numbers. I believe that there is a service which will reprint a thesis paper for a fee, and USnail it. I've no idea the name of the service. In short can anyone provide pointers to the thesis, or possibly, any books which cover this or similar programs? Specifically, I wish to learn about programs that deal with meta-rules and meta-meta-rules, rather than rules. Was that as clear as MUD? Danny -- Daniel S. Cox ({siesmo!gatech|ihnp4!akgua}!itm!danny) ------------------------------ Date: 24 May 86 01:43:40 GMT From: allegra!princeton!caip!seismo!mcvax!ukc!reading!brueer!holte@ucbvax .berkeley.edu (Robert Holte) Subject: Re: AI in IAsfm > In the June 86 issue of IAsfm ,there's a fascinating article on AI and > common sense. In this article, the author mentions a program called > Eurisko, ... > How can I find out more about it? > > Steven Grady Douglas Lenat has written and exercised two heuristic "discovery" programs, AM and EURISKO. His initial exploration of the problem of heuristic (mechanical) discovery constituted his Ph.D. research and culminated in the somewhat controversial program, AM. After his thesis, Lenat analyzed the shortcomings and strengths (or "sources of power" as he came to call them) of AM, and from this analysis EURISKO was conceived. Unfortunatley, since Lenat's move from Stanford to MCC (Austin) a year or two ago, he has ceased working with EURISKO. I am aware of one or two isolated, low-profile projects to build EURISKO-like systems. Most notable is the work of Ken Haase at MIT on a system called CYRANO -- but I don't think any of Haase's work has yet been published. -- Rob Holte UUCP: ...!mcvax!ukc!brueer!holte ARPANET, CSNET, JANET: holte@ee.brunel.ac.uk Dept. of Electrical Engineering Brunel University England UB8 3PH EURISKO References: (Lenat is the sole or first author in all cases) (1) Artificial Intelligence journal, vol.21, nos.1,2, 1983 (two articles: pp.31-59, pp.61-98) MOST COMPREHENSIVE ACCOUNT AVAILABLE, includes a description of the program and its applications (2) Lenat's chapter (pp. 243-306) in the book "Machine Learning" (volume 1), edited by R.S. Michalski, J.G. Carbonell, and T.M. Mitchell, Tioga Press, 1983 (3) The AI Magazine, vol.3, no.3, 1982 (summer), pp.17-33 CONCENTRATES ON THE APPLICATION of Eurisko to the discovery of new VLSI microcircuit structures (4) SIGART Newsletter (ACM Special Interest Group on AI), No. 79, 1982 (January), pp.16-17 Anecdotal account of EURISKO's success in designing a "fleet" which won a national wargame tournament (5) "Why AM and EURISKO Appear to Work", Lenat and J. Seely Brown, Artificial Intelligence journal, vol.23, no.3 (1984), pp.269-294 AN INSIGHTFUL ANALYSIS of the success of Lenat's 2 programs ------------------------------ Date: Fri, 23 May 86 17:29:02 edt From: Derrell Piper Subject: Re: VAX VMS LisP > Are there any Common LisPs for the VAX under VMS? (DEC's VAX LisP is an > Ultrix product only, so far as I know.) > > If there's no (decent) Common LisP, what is the best choice? > > Larry @ jpl-vlsi.arpa Digital does market a version of Lisp that runs under VMS. I have version 1.2 on a ninty-day trial license. Derrell Piper 120 Rosenau Hall (201H) School of Public Health University of North Carolina - Chapel Hill Chapel Hill, NC 27514 (919) 966-5106 Bitnet: derrell@uncsphvx.BITNET Usenet: ...decvax!mcnc!ecsvax!hobbit ------------------------------ Date: Wed, 21 May 86 08:55 EST From: RLH Subject: RE: VAX VMS LISP In AILIST 4-124, Larry@JPL-VLSI,ARPA asks about availability of Common LISP on VAX/VMS. I don't know where you got your information, but DEC sells a good version of Common LISP that runs under VMS or microVMS. As far as I have seen, it is a complete and faithful implementation with some additions for accessing system routines and calling code written in other languages. There is also a package that DEC calls tha AI Workstation that consists of a VAXstation, Common LISP, and some LISP software to do window-oriented editing, etc. on the bit-mapped display of the VAXstation. I haven't used this yet, so I cannot comment. I have heard that there will be Flavors and Common LOOPS available as well, but haven't seen any hard evidence of this. DEC appears to be firmly committed to Common LISP (any DECies care to comment?). They even use Guy Steele's book "Common LISP" as part of the documentation. Bob Haar G. M. Research Labs ------------------------------ Date: 20 May 86 16:06:37 GMT From: decwrl!pyramid!pesnta!phri!cmcl2!harvard!knight@ucbvax.berkeley.edu Subject: Conway's LIFE (My e-mail didn't work, so I am posting to the net...) There is a very good, very recent book on LIFE called "The Recursive Universe" by William Poundstone, c 1985, William Morrow and Company, publishers. The book doesn't contain any original LIFE discoveries, but rather presents the great bulk of work on LIFE in the context of modern physics, computation, and recursion. Kevin Knight (knight@harvard) ------------------------------ Date: 22 May 86 17:57:28 GMT From: tektronix!tekgen!stever@ucbvax.berkeley.edu (Steven D. Rogers) Subject: RE: LIFE references Another more general book that mentions the game of Life in the broader context of games and life: Laws of the Game, How the Principles of Nature Govern Change by Manfred Eigen, and Ruthild Winkler, Harper Colophon Books l981 It was sort of advertised as a "Godel, Escher, Bach" of games. I don't think it quite made that level, but it is an interesting book. ------------------------------ Date: 13 May 86 23:50:41 GMT From: ihnp4!alberta!tony@ucbvax.berkeley.edu (Tony Marsland) Subject: International Computer Chess Association Journal The current (March 1986) issue of the ICCA Journal has been received. Aside from the following three technical articles, there are reports on Ken Thompson's 5-piece endgame studies, showing that several endgames are won in more than 50 moves, plus the usual reviews and short articles. There is also an extensive study of most commercially available chess machines by a Swedish group. This list is the most accurate and scientific estimate of the relative playing strength of those programs. The major articles are "A review of game-tree pruning" by T.A. Marsland "An overview of machine learning in computer chess" by S.S. Skiena "A data base on data bases" by H.J. van den Herik and I.S. Herschberg Information on the availability of this journal has been posted before. ------------------------------ Date: 22 May 86 19:05:00 GMT From: pur-ee!uiucdcs!kadie@ucbvax.berkeley.edu Subject: $1,000,000 Prize This might be of general interest: /* May 17, 1986 by chen@uiucdcsb.CS.UIUC.EDU in uiucdcs:uiuc.ai */ /* ---------- "$1,000,000 for a program" ---------- */ The following was posted in net.game.go. In case you don't know about Go, it is an ancient oriental board game played between two players on a 19 by 19 grid. The best Go program so far is no better than an intellegent novice that has received only one week intensive training. /* May 14, 1986 by alex@sdcrdcf.UUCP in uiucdcsb:net.games.go */ /* ---------- "Million $ prize" ---------- */ I think this is a big news for the go community. The Chinese Wei Chi(go in Chinese) Association(TWCA) in Taipei, Taiwan and conjunction with one of Taiwan's largest computer company have put 2 million US dollar in trust as prize money of computer go games. The top standing prize is 1 million dollar for any computer go game defeating reigning junior champion in Taiwan. The prize offer is good for 15 years. (BTW, if you are wondering how they raise the prize money, take a look at all the cheap IBM PC clones around.) The prize money is much more interesting the Fredkin's prize. They are other prizes for the computer go champion, etc. The TWCA is the first organization offering prize money for computer-computer and computer-human competition, according to my and the computer go game pioneer Bruce, who appeared in TWCA first computer tournament last January. Bruce lost twice and did not place in top five. That tournament offered 2 to 3 thousand price money to the winner. His first loss was to a go game written in BASIC running on an Apple. Bruce was winning convincingly until the Apple games made a suicide move which is legal under Chinese rule but not under Japanese rule. Bruce's game went into loop. The judge allowed Bruce to fix his code on the spot as long as he can make the move before his time clock runs out. (They did not want Bruce to lose because he was the main attraction, and I believe they paid him some appearance fee.) But Bruce did not fix it right within the 30 minutes he had. I did not stick around for his second loss. Bruce's game was running on a 8MHz PC clone. If you are interested in entering the next competition which is in November, you better get the rule book on the Chinese rules, which differ slightly from Japanese in area like suicide moves and scoring. Last competition was restricted to personal computer, although I find big disparity in computer power between a MacIntosh and an Apple II. However, I don't think computing power is the main bottleneck right now. If there are enough people interested, I can get additional detail about the tournament. Also, a junior champion in Taiwan is about 1 dan in Chinese amateur rating, which is about 5-6 dan in US and Japanese amateur rating. Bruce's game was last rated to be 19Q in Japan human tournament. He said he may push it to 11-12Q by November. I think Bruce has got a good technique but his potential is limited by his knowledge of go. But at any rate, you have your work cut out for you. Alex Hwang /* End of text from uiucdcsb:net.games.go */ /* End of text from uiucdcs:uiuc.ai */ ------------------------------ Date: Thu 15 May 86 18:24:51-PDT From: John Myers Subject: IT*S Grammar Sir: I am writing to protest the continual misuse of the word "its" for the third person neuter posessive, when everyone knows its the contraction for "it is". I's hair stands on end everytime I see someone use it in they's sentence. Ive even heard one grammarian state that he's book says that personal pronouns all have a special posessive case form that doesnt use "apostrophe-S"--hes off he's rocker! Youre well aware whatll happen to you's reading material if this becomes common. Were going to have to keep we's guard up, until its clear that peopleve gotten this straight! Its dreadful!! Not only that, some peoplere even forming they's contractions with an apostrophe. When they have a word phrase such as "it is", and they want to write it's contraction, they's spelling is "it's"!! Ill never see where they couldve gotten such atrocious grammar from, when if theyre unsure of how to use "its", they only have to look it's meaning up in they's dictionary!! Instructor: "My word! Where's your grammar, boy?" Youth: "Watching soap on the TV." John Myers~~ ------------------------------ Date: Thu 15 May 86 18:56:44-PDT From: John Myers Subject: Etymology of Foo-Bar Item of interest: FUBAR was originally an acronym for "Fouled" Up Beyond All Recognition, stemming from the W.W.II era. It is related to SNAFU, and such short-lived acronyms as FUBIO, FUBISO, GFU, JANFU, MFU, SAMFU, SAPFU, SNEFU, SUSFU, TARFU, and TUIFU. Source: A Dictionary of Euphemisms & Other Doubletalk, Rawson. ------------------------------ Date: 13 May 86 15:41:39 GMT From: tektronix!uw-beaver!bullwinkle!rochester!rocksanne!sunybcs!ellie !colonel@ucbvax.berkeley.edu (Col. G. L. Sicherman) Subject: Re: Plan 5 for Inner Space > Answers: about nine months, plus a few years training. And hospitals are > charging on the order of $1000 now; but the care and feeding of the project > will cost more. You do get a tax break. Warning: the U.S. government no longer allows private ownership of these units. Possession is permitted but subject to a long-term time limitation which is determined on a case-by-case basis. "Well, Doctor Eccles, how are the men feeling? Any cases of frozen feet?" "Duh, you didn't order any cases of frozen feet." -- Col. G. L. Sicherman UU: ...{rocksvax|decvax}!sunybcs!colonel CS: colonel@buffalo-cs BI: csdsicher@sunyabva ------------------------------ End of AIList Digest ******************** From vtcs1::in% Wed May 28 14:31:06 1986 Date: Wed, 28 May 86 14:30:59 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #131 Status: R AIList Digest Tuesday, 27 May 1986 Volume 4 : Issue 131 Today's Topics: Queries - Functional Programming and AI & Parallel Logic Programming & Information Modeling for Real-Time/Asynch Processes AI Tools - PROLOGs & Common LISPs & Common LISP Style Standards, Expert Systems - Economics of Development and Deployment ---------------------------------------------------------------------- Date: 21 May 86 13:14:00 EST From: "CUGINI, JOHN" Reply-to: "CUGINI, JOHN" Subject: Functional programming and AI Here's a (dumb?) question for assorted AI wizards: how (if at all) does functional programming support AI type applications? By "functional programming", I mean the ability of a language to treat functions (or some other embodiment of an algorithm) as a data object: something that can be passed from one routine to another, created or modified, and then applied, all at run-time. Lisp functions are an example, as is C_Prolog's ability to construct predicates from lists with the =.. operator, and the OPS5 "build" action. Do working AI programs really exploit these features a lot? Eg, do "learning" programs construct unforeseen rules, perhaps based on generalization from examples, and then use the rules? Or is functional programming just a trick that happens to be easy to implement in an interpreted language? Thanks for any thoughts on this... John Cugini Institute for Computer Sciences and Technology National Bureau of Standards ------------------------------ Date: 25 May 86 14:26:49 GMT From: wisdom.BITNET!jaakov@ucbvax.berkeley.edu (Jacob Levy) Subject: Parallel Logic Programming Dear fellow AIListers and PrologListers, I'm interested in obtaining the latest references you may have to articles concerned with Parallel Logic Programming languages. If you have recently written an article concerned with parallel execution of Prolog or about a committed-choice non-deterministic LP language, I'm interested to read it, or at least to receive a pointer to the article. By RECENT I mean articles which have been published in 1985 and 1986 or which are about to appear. I am interested in any and all sub-topics of the fields listed above. Thank you very much ahead of time for your response, Rusty Red (AKA Jacob Levy) BITNET: jaakov@wisdom ARPA: jaakov%wisdom.bitnet@wiscvm.ARPA CSNET: jaakov%wisdom.bitnet@csnet-relay UUCP: (if all else fails..) ..!ucbvax!jaakov%wisdom.bitnet ------------------------------ Date: 24 May 86 00:10:04 GMT From: amdcad!cae780!leadsv!rtgvax!ramin@ucbvax.berkeley.edu Subject: Information Modeling for Real-Time/Asynch processes Sorry about all the cross-postings but I'm trying for the widest circulation short of net.general (:-) I am looking for any pointers to literature/specifications/ideas for Modeling of asynchronous and/or real-time systems. These would be very high-level design specification tools to help model parallel real-time events and systems. Intuitively, at least I think the way to go is Temporal Logics (hence the net.philosophy posting...) however, that seems to be currently applied only to hardware design (CIRCAL et al). The problem with the standard dataflow diagram and associated descriptive systems is their failure to capture at least simultaneous (ideally, parallel) events. On the other hand, the rigor with which one would want to model such an event lends itself to creative Knowledge Representation techniques (hence net.ai and net.cog-eng...) and even possibly many-valued logics...? To put it in some more perspective, the model would be of some complicated industrial processes that up to now have been modeled in a synchronous i.e. serialized fashion. I would like to see if there are any references out there to attempts at asynchronous modeling. Would definitely repost (to where? (:-) if there are enough responses... Thanks much... ramin : alias: ramin firoozye' : USps: Systems Control Inc. : : uucp: ...!shasta \ : 1801 Page Mill Road : : ...!lll-lcc \ : Palo Alto, CA 94303 : : ...!ihnp4 \...!ramin@rtgvax : ^G: (415) 494-1165 x-1777 : ------------------------------ Date: 16 May 86 10:53:22 GMT From: allegra!mit-eddie!genrad!panda!husc6!harvard!seismo!mcvax!ukc!kcl-cs !glasgow!dunbar@ucbvax.berkeley.edu (Neil Dunbar) Subject: Re: looking for Prolog > I'm looking for a version of Prolog. The machines available to me > include an AT&T 7300 (Unix PC), AT&T 3B5, AT&T 3B2, Plexus P/60, Plexus > P/35, IBMPC, and AT&T 6300PC (IBMPC compatible). I've spoken with > someone from AT&T who suggests that Quintus may be porting to the 7300. > I've spoken with someone from Quintus who says there is no port and no > contract at this time. I've heard of something called C-Prolog, but > don't know for sure what it is. ... Don't Borland make a version of Prolog to run on the PC, Turbo Prolog? If you want a compiler there is the Arity compiler, again for MS-DOS systems, but it costs a few thousand (dollars or pounds, depending on which side of the Atlantic you're on). CProlog V1.2 is the current prolog interpreter system from the University of Edinburgh, running on our 11/780 under Unix. I don't know if it can be ported onto the machines you describe, but you never know, anything's possible. If you want to learn Prolog, try Clocksin & Mellish "Programming in Prolog", which is an excellent tutorial guide. Hope this helps, Neil Dunbar. ------------------------------ Date: Sat, 24 May 86 02:35:00 +0200 From: enea!zyx!jeg@seismo.CSS.GOV Subject: Re: Logic/Functional Languages? In article <8605200626.AA27699@ucbvax.Berkeley.EDU> you write: >Does anyone on the list know of available languages incorporating both >logic and functional programming (preferably in a Unix 4.2 environment >or possibly an IBM/PC)? ... Answer to the questions: 1.) Does anyone on the list know of available languages incorporating both logic and functional programming...? 2.) Some version of Prolog embedded within Common Lisp...? 3.) Has anyone produced any large applications with these hybrid systems? Are the benefits derived from the systems *significant* (over using, say, vanilla lisp or prolog)? Hewlett-Packard have informally introduced HP Prolog to some customers and the official introduction is scheduled to be sometime in August. HP Prolog is residing on top of HP Common Lisp and this development environment is therefore incorporating both Common Lisp and Prolog. Since I am affiliated with HP, the following information is biased and might sound like an advertisment, but I'll try to answer the third question without breaking to many ethical rules for the net. HP Development Environment is based on HP-UX (Unix V.2) and HP 9000 series 300, a 68020 based machine, with HP:s window system. Top level for the Development Environment: - A complete EMACS editor with some enhancements. - A general browser. Main features with the Development Environment are: - The high level of integration - The ability to use both Common Lisp and Prolog in the same process and on the same objects and to mix Common Lisp and Prolog code. HP Common Lisp has: - Interpreter and compiler - Objects package - Ability to call C/Pascal/Fortran - Debugger - Interrupt handler HP Prolog consists of two different environments: - A "Common Lisp compatible" S-expression syntax - Edinburgh C-Prolog syntax HP Prolog has: - Interpreter - Incremental compiler - Block optimzing compiler - Debugger Main features of HP Prolog are: - A much extended Prolog - Ability to mix Prolog and Common Lisp - Macros - Packages - Mode declarations - Declarative determinism - Integration in the environment - A well-designed and complete I/O system - Other minor features like strings, graphics etc. - An extended Definite Clause Grammar (DCG) - Respectable performance The Prolog system will soon be available with/without Common Lisp system on other vendors machines. Quite large applications on this system are currently under development. There is definitely a significant advantage of being able to mix Common Lisp and Prolog. Common Lisp and Prolog have both different advantages and complement instead of excluding each other. Jan-Erik Gustavsson, ZYX AB, Styrmansgatan 6, 114 54 Stockholm, Sweden Phone: + 46 - 8 - 65 32 05 ...mcvax!enea!zyx!jeg ------------------------------ Date: 18 May 86 00:52:32 GMT From: allegra!mit-eddie!genrad!panda!husc6!harvard!caip!lll-crg!seismo !mcvax!enea!kuling!martin@ucbvax.berkeley.edu (Erik Martin) Subject: Re: Common LISP style standards. In article <2784@jhunix.UUCP> ins_amrh@jhunix.UUCP writes: > > - How do you keep track of the side effects of destructive functions > such as sort, nconc, replaca, mapcan, delete-if, etc? Don't use them. I use destruction only when I need circular objects or when I need to speed up a program. In the latter case I write it strictly functional first and then substitute 'remove' with 'delete' and so on. This should not affect the semantics of the program if it is 'correctly' written from the beginning. But it's really a task for the compiler so You shouldn't need to think about it. > - When should you use macros vs. functions? I only use macros when I need a new syntax or a 'unusuall' evaluation of the arguments. (like FEXPR in Franz and MacLisp.) > - How do you reference global variables? Usually you enclose it > in "*"s, but how do you differentiate between your own vars and > Common LISP vars such as *standard-input*, *print-level*, etc? Always "*"s. No differentiation. > - Documentation ideas? An 'overview' description in the file header, more detailed on top of each function. Very few comments inline, use long function and variable names instead. Documentation strings in global variables and top level (user) functions. > - When to use DOLIST vs MAPCAR? Quite obvious. Use DOLIST when you want to scan through a list, i.e. just look at it. At the end of the list it returns NIL or the optional return form. You can also return something with en explicit RETURN. Use MAPCAR when you want to build a *new* list with a function applied to each element. > - DO vs LOOP? Write what you mean. If you mean 'repeat until doomsday' (without any variables bound) then use LOOP. > - Indentation/format ideas? Or do you always write it like the > pretty-printer would print it? A lot of white space in the code. The rest is very personal and hard to set up rules for. Nice editors usually have good ideas about how it should look. > - NULL vs ENDP, FIRST vs CAR, etc. Some would say "FIRST" is > more mnemonic, but does that mean you need to use > (first (rest (first X))) instead of (cadar X) ?? Again, write what you mean. If you mean 'is this the end of the list we are just working with?' then use ENDP, if you mean 'is this NIL (an empty list)?', use NULL, and if you mean 'is this false?' use NOT. Write FIRST if you mean the first element of a list, SECOND for the second, THIRD for the third...and combinations of these when appropriate. At some limit this gets very messy though, and C*R is better. But in that case you perhaps should write your own accessor functions. When working with cons'es I always use CAR and CDR. My general rule is : Write what you mean and leave the task of efficiency to the implementation and compiler. Per-Erik Martin -- Per-Erik Martin, Uppsala University, Sweden UUCP: martin@kuling.UUCP (...!{seismo,mcvax}!enea!kuling!martin) ------------------------------ Date: Sat, 24 May 86 08:23:25 est From: munnari!psych.uq.oz!ross@seismo.CSS.GOV (Ross Gayler) Subject: economics of expert systems - summary of replies A while back I put out a request for information on the economics of the development and deployment of expert systems. This is a summary of the replies I have received. I received around ten replies, most of which were of the 'please let me know' variety. Some of these went to some length to indicate that they felt this was an important area. It does seem that there is a need for this information and it either doesn't exist or somebody is not sharing it. There were three substantive replies which told of: 1 A company which attempted to develop three expert systems. One took twice as long to develop as the FORTRAN program it replaced, the second was too slow to be usable, and the other was abandoned for lack of an expert. 2 A successful family of expert systems that are widely used in-house. The point made here was that the development cost was an insignificant fraction of the cost of packaging the product for deployment and the continuing cost of training the users. 3 A pointer to the November 1985 IEEE Transactions on Software Engineering which was a special issue on "Artificial intelligence and software engineering". I found the articles by Doyle, Bobrow, Balzer, and Neches et al to be the most relevant to my needs. Doyle argues that the productivity advantage of the artificial intelligence approach comes from the tools and techniques used to construct the product, not from the ultimate form of the product itself. The other papers do not explicitly address the modelling of costs. However, an implicit model is discernible from the areas they choose to emphasize. I will send a request to the software engineering list and see if I can get any joy there. If not it looks like I might be forced to do some work for myself. What I would like is a predictive model which will give me the costs to implement and deploy an expert system or conventional system as functions of various features of the problem, the tools available, and the development and deployment environments. As I do not have any empirical data the best I can aim for is a set of statements on the qualitative shapes of the cost curves for various factors. Using these curves backwards would allow me to say what problem characteristics are a lot more conducive to an expert system solution being cheaper than a conventional solution. I will probably start with the cost models in Tom de Marco's book, "Controlling software projects" and try to identify expert systems analogues of the cost factors he identifies for conventional systems. If I manage to get anywhere with this I will let you know. Ross Gayler | ACSnet: ross@psych.uq.oz Division of Research & Planning | ARPA: ross%psych.uq.oz@seismo.css.gov Queensland Department of Health | CSNET: ross@psych.uq.oz GPO Box 48 | JANET: psych.uq.oz!ross@ukc Brisbane 4001 | UUCP: ..!seismo!munnari!psych.uq.oz!ross AUSTRALIA | Phone: +61 7 227 7060 ------------------------------ End of AIList Digest ******************** From vtcs1::in% Thu May 29 00:49:23 1986 Date: Thu, 29 May 86 00:49:17 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #132 Status: R AIList Digest Wednesday, 28 May 1986 Volume 4 : Issue 132 Today's Topics: Queries - AI Survey & AI Applications in Simulation & Neural Networks, Brain Theory - Chaotic Neural Networks, Logic Programming - Functional Programming & Prolog Variables, AI Tools - VAX LISP on VMS and ULTRIX, Binding - Sussex Cognitive Studies, Literature - Object-Oriented Programming Book, Psychology - Doing AI Backwards ---------------------------------------------------------------------- Date: 23 May 86 15:32:39 GMT From: mcvax!ukc!reading!onion.cs.reading.AC.UK!scm@SEISMO (Stephen Marsh) Subject: A survey on AI I am currently doing a survey on the attitudes and beliefs of people working in the field of AI. It would be very much appreciated if you could take the time to save this notice, edit in your answers and post me back your reply. If there are any interesting results, I'll send them to the net sometime in the future. -Thanks 1. Do you, or have you, undertaken any research in the field of Artificial Intelligence?..... 2. In which country was the research undertaken?..... 3. For how long did your research continue?..... 4. If you are not currently working in the field of AI, when was the period of your research?..... 5. What area of research did your work cover? (eg IKBS)..... 6. Were you satisfied with the results of your research?.... 7. Did your research make you feel that in the long term AI was not going to succeed in creating an intelligent machine?.. 8. Do you find the progress of research in AI in the last 5 years?...... 10 years?..... 25 years?..... acceptable? 9. What do you consider the main objectives of AI?..... 10. Excluding financial pressures, do you consider that AI researchers should reconsider the direction of their work?..... 11. Do you consider that the current areas of research will eventually result in an 'intelligent' machine?..... 12. Do you consider that the current paradigm of humans producing cleverly-written computer programs can ever fulfil the initial aim of AI of producing an intelligent machine in the accepted sense of the word 'intelligent'?..... 13. Should a totally new approach to producing an intelligent machine be found, not based simply on sets of sophisticated programming techniques?..... scm@onion.cs.reading.ac.uk Steve Marsh Dept of Computer Science, PO Box 220, University of Reading, Whiteknights, READING ,UK. ------------------------------ Date: 23 May 86 05:12:27 GMT From: shadow.Berkeley.EDU!omid@ucbvax.berkeley.edu (Omid Razavi) Subject: AI applications in simulation I am interested in the applications of AI in simulation. Specially, I'd like to know if there are expert system environments today that would support simulation modeling and provide features similar to those of standard simulation languages such as GASP IV and SIMSCRIPT. Also, references to technical articles related to this subject is greatly appreciated. Omid Razavi omid@shadow.berkeley.edu ------------------------------ Date: 17 May 86 14:39:34 GMT From: hplabs!qantel!lll-lcc!lll-crg!seismo!mcvax!ukc!warwick!gordon@ucbvax .berkeley.edu Subject: Re: neural networks This may be a bit of a tangent, but I feel it might have some impact on the current discussion. The mathematical theory of chaotic systems is currently an active area of research. The main observation is that models of even very simple systems become chaotic in a very small space of time. The human brain is far from being a simple system, yet the transition to chaos rarely occurs. There must be a self-correcting element within the system itself, as it is often perturbed by myriad external stimuli. Is the positive feedback mentioned in article <837@mhuxt.UUCP> thought to be similar to the self-correcting mechanisms in the brain? Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon ------------------------------ Date: 23 May 86 14:51:53 GMT From: hplabs!hplabsc!kempf@ucbvax.berkeley.edu (Jim Kempf) Subject: Re: neural networks > The mathematical theory of chaotic systems ... > Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon Not having seen <837@mhuxt.UUCP>, I can't comment on the question. However, I do have some thoughts on the relation between chaos in dynamical systems and the brain. The "chaotic" dynamical behavior seen in many simple dynamical systems models is often restricted to a small region of the state space. By a kind of renormalization procedure, this small region might be topologically shrunk, so that, from a more macroscopic view, the chaotic region actually looks more like a point attractor. Another possibility is that complex systems like the brain are able to perform a kind of ensemble averaging to filter out chaos. Sorry if this sounds like speculation. Jim Kempf kempf@hplabs ------------------------------ Date: Tue, 27 May 86 18:10:25 PDT From: narain@rand-unix.ARPA Subject: Functional and Logic Programming Reply to Paul Fishwick regarding a language which incorporates both functional and logic programming, (AIList digest v.4 #124.): In a recent paper "A technique for doing lazy evaluation in logic" I describe a method of defining functions in a logic-based language such as Prolog. It is shown how we can keep Prolog fixed, but define functions in such a way that their interpretation by Prolog directly yields lazy evaluation. This contrasts with conventional approaches for doing lazy evaluation which keep the programming style fixed but modify the underlying interpreter. More generally the technique can be viewed as a natural and efficient method of combining functional and logic programming. The paper appeared in 1985 IEEE Symposium on Logic Programming, and a substantially expanded version of it is to appear in the Journal of Logic Programming. Sanjai Narain Rand Corp. ------------------------------ Date: 22 May 86 07:46:51 GMT From: amdcad!lll-crg!booter@ucbvax.berkeley.edu Subject: Prolog and Thank you WOW! I didn't realize so many folks out there have played with prolog. I received all sorts of replies, most very useful in explaining the instantiation of variables to values (I hope I worded it properly). PASCAL doesn't prepare you for it and I write LISP code by the grace of God(it just works, I dunno why!). A major problem I had was in the idea of reconsulting a file. I just kept loading copies of files in there and of course would get the same error message as it seemed to be reading the first one over and over. I have passed that phase now and am endeavoring to master the idea of using the "cut". You'd all be proud of me, I wrote a very simple version of the computer that talks back (called "doctor" or "eliza"). I still like LISP better, but at least I am no longer swearing at the terminal. Thank you all very much E ***** ------------------------------ Date: 27 May 86 15:48:00 EST From: "LOGIC::ROBBINS" Reply-to: "LOGIC::ROBBINS" Subject: VAX LISP is supported on both VMS and ULTRIX VAX LISP V2.0 (DEC's current release of Common Lisp) is supported on VMS and ULTRIX. I hope that this clears up any confusion resulting from two incorrect messages that appeared in this list recently concerning VAX LISP. Rich Robbins Digital Equipment Corporation 77 Reed Rd. HL02-3/E09 Hudson, MA 01749 Arpanet: Robbins@Hudson.Dec.Com ------------------------------ Date: Thu, 22 May 86 08:39:30 gmt From: Aaron Sloman Subject: Sussex Cognitive Studies mail address This is to confirm that the Sussex Cognitive Studies Netmail address has finally(?) settled down to UK.AC.SUSSEX.CVAXA. Arpanet users can try: aarons@cvaxa.sussex.ac.uk (UK uses the reverse of ARPA order) or, if that doesn't work: aarons%uk.ac.sussex.cvaxa@ucl-cs or aarons%uk.ac.sussex.cvaxa@cs.ucl.uk.ac or via UUCP: ...mcvax!ukc!cvaxa!aarons Other users at this address include Chris Mellish (chrism), Margaret Boden(maggieb), Ben du Boulay (bend), Jim Hunter (jimh), Gerald Gazdar(geraldg), John Gibson (johng), David Hogg (daveh), and the new POPLOG Project manager Alan Johnson (alanj). Aaron Sloman ------------------------------ Date: Tue 13 May 86 18:37:50-PDT From: Doug Bryan Subject: object-oriented programming books [Forwarded from the Stanford bboard by Laws@SRI-AI.] Brad Cox's book "Object-Oriented Programming: An Evolutionary Approach" is now out. The book is published by Addison Wesley. doug ------------------------------ Date: 18 May 86 05:39:39 GMT From: ernie.Berkeley.EDU!tedrick@ucbvax.berkeley.edu (Tom Tedrick) Subject: Doing AI backwards (from machine to man) More on Barry Kort's "Problem of the right-hand tail" (ie social persecution of those with high intelligence). Here is the way I look at the problem. In order to function in society, it is necessary for most individuals to operate in a more or less routine manner, performing certain acts in a repetitive manner. I have been trying to work backwards from models of computation, abstracting certain principles and results in order to obtain models with a wider application, including social behavior. This is somewhat the reverse direction from that taken by those working in Artificial Intelligence, who study intelligent behavior in order to find better ways for machines to function. I am studying how machines function in order to find better ways for humans to function. Anyway, most people in society functioning more or less automatically, they handle input in such a way that only information relevant to their particular problems is assimilated. Input is interpreted according to the pre-existing patterns in their minds. It is as if it was formatted input in fortran, anything that doesn't conform to certain patterns is interpreted nonsensically. The people in the "right-hand tail", IQ distribution-wise, are there primarily due to greater capacity for independent thought, abstract thought, capacity to reason for themselves (or so I claim). Thus these individuals are more likely to have original ideas which don't conform to the pre-existing patterns in the minds of the more average individuals. The average individual will become disturbed when presented with information which he cannot fit into his particular format. And with good reason, since his role is to function as an automaton, more or less, he would be less efficient if he spent time processing information unrelated to his tasks. So by presenting original information to the average individuals in society, the "rightie" is likely to be attacked for disturbing the status quo. To use the machine analogy, the "righties" are more like programmers, who alter the existing software, where the "non-righties" are like machines which execute the instructions they already have in storage. The analogy can be pushed in various ways. We can think of each individual as being both programmer and machine, the faculty of independent judgement and the self being the programmer or system analyst, while the brain is the computing agent to be programmed. The individual is constantly debugging and rewriting the code for his brain, by the choices he makes which become habits, and so on. Also, in interactive protocols where various individuals exchange information, each is tampering with the software of the other. I currently have been working out a strategy for dealing with those I live with who talk too much. It is like having a machine which keeps spewing out garbage every time you give it some input. My current strategy is to carry a little card saying "I am observing silence. I will answer questions in writing." This seems to work very well, it is as if this form of input goes through another channel which does not stimulate so much garbage in response. Or its like saying "the network is down today, so sorry." One last tangent. Note that in studying models of computation one of the primary costs is the cost of memory. We can turn this observation to good use in studying human behavior. For example, suppose your wife asks you to pick up some milk at the store after work. This seems a reasonable enough request, on the surface. But if you think of the cost in terms of memory, suppose short term memory is extremely limited and you have to keep the above request stored in short term memory all day. In effect you are reducing your efficiency in all the tasks you perform all day long, since you have less free space in your short term memory. Thus we see again how women have a brilliant gift for asking seemingly innocent favors which are really enormously costly. The subtle nature of the problem makes it difficult to pin down the real poison in their approach. [Anything held in short-term memory for five seconds automatically enters long-term memory as well. If the man chooses to keep refreshing it in STM, perhaps due to poor LTM retrieval strategies, he needs to take a course in memory techniques -- it's hardly the woman's fault. -- KIL] You can use various strategies in order to deal with this problem. One is to use some external form of storage (like writing it down in a datebook), and having a daemon which periodically wakes up and tells you to look in your external storage to see if anything important is there. Of course this also has its costs. By virtue of the relative newness of computer science, I think there will be opportunities for applying the lessons we have learned about machine behavior to other fields for some time to come. (Since it is only recently that the need for rigorous treatment of models of computation has induced us to really make some progress in understanding these things.) ------------------------------ End of AIList Digest ******************** From vtcs1::in% Thu May 29 00:49:34 1986 Date: Thu, 29 May 86 00:49:29 edt From: vtcs1::in% (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #133 Status: R AIList Digest Wednesday, 28 May 1986 Volume 4 : Issue 133 Today's Topics: Reviews - Spang Robinson Report, Volume 2 No. 5 & International Journal of Intelligent Systems, Logic Programming - Benchmarking KBES-Tools, Policy - Abstracts of Technical Talks, Seminars - Analogical and Inductive Reasoning (SU) & Reasoning about Semiconductor Fabrication (SU) & Levels of Knowledge in Distributed Computing (SU) ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Spang Robinson Report, Volume 2 No. 5 Summary of Spang Robinson Report, May 1986 Volume 2, 1986 __________________________________________________________________________ AI at Darpa, the U. S. Department of Defense's Advanced Research Projects Agency This year, DARPA will devote $60 million dollars to AI research. 26 million of this is for basic AI research not included in Strategic computing, 22 million is for technology base research in Strategic Computing and 25 million is for large prototype applications in Strategic computing. In 1985, 47.5 percent of the research went to industry with 40.7 to universities with the remainder going to government agencies and federal contract research institutes. Oak Ridge National Labs is developing a system to assist in the analysis of budgets. List of DARPA projects in AI Autonomous Land Vehicle project Integration - Martin Marietta Terrain Data Base - ETL Vision Based Navigation - University of Maryland ALV Route Planning Research - Hughes Laboratory Telepresence System - Vitalink Navy battle Management Force Requirements Expert System - TI Spatial Data Management System - CCA Combat Action Team - Naval Ocean Systems Center, CMU Fleet Command Center Battle Management - NOSC Commander's Display Technology - MIT Pilot's Associate (two teams) Team 1: Lockheed, General Electric, Goodyear Aerospace, Teknowledge, CMU, Search Technologies Defense Systems Team 2: McDonnel Aircraft, TI AirLand Battle Management System Technology definition - MIT Soldier-Machine Interface - Lockheed Natural Language Training Aid - Cognitive Systems AI Planning System - Advanced Decison Systems Message Fusion - LOGICON Knowledge Engineering - BDM Butterfly Benchmarking - BRL/ Los Alamos Labs Interpretation of Reconnaissance Images (SAIC, Advanced Decision Systems, TASC, MRJ, Mark Resources, Hughes Aircraft) Multiprocessor System Architectures Tree Machines - Columbia University Software Workbench - CMU Programmable Systolic Array - CMU ADA Compiler Systems - FCS, Inc Synchronous Multiprocessor Architecture - Georgia Tech High Performance Multiprocessor - University of California at Berkeley VLSI design - University of Southern Carolina Common Lisp Framework - USC-ISI Data Flow Emulation Facility - MIT Massive Memory Machine - Princeton University Connection Machine - Thinking Machines Natural Language (BBN, System Development Corporation, University of Massachussetts, University of Pennsylvania, USC-ISI, New York University, SRI) Expert System Technology (BBN, General Electric, Intellicorp, University of Massachusetts, Tecknowledge, Ohio State University, Stanford University) Speech Understanding "250 word speaker-independent system with a large vocabulary" was demonstrated in 1986 Real Time Speech - BBN Continuous Speech Understanding - CMU Auditory Modelling - Fairchild Acoustic Phonetic-Based Speech - Fairchild Speech Data Base - TI Acoustic Phonetics - MIT Tools for Speech Analysis - MIT Speech Data Base - MIT Robust Speech Recognition - Lincoln Labs Speech Co-Articulation - NBS Speaker Independence - SRI Computer Vision Optical Avoidance and Path Planning - Hughes Research Laboratory Parallel Algorithms - CMU Terrain Following - CMU Dynamic Image Interpretation - University of Massachusetts Target Motion and Tracking - USC Reasoning, Scene Analysis - Advanced Decision Systems Parallel Algorithms - MIT Spatial Representation Modelling- SRI Parallel Environments - University of Rochester Also: Compact Lisp Machine - Texas Instruments __________________________________________________________________________ Japan Watch ICOT is developing a new personal use Prolog work station called PSI-II which will be smaller and faster than the first version, PSI-I. PSI-II is targeted to cost $55,500. 60 PSI units have already been installed and the version 2.0 of the operating system has been replaced. Sega Enterprises will market in mid-April a Prolog-based personal computer for CAI for children in elementary school. Nippon Steel Corporation and Mitsubishi have been testing PROLOG for process control software. At the Information Processing Society of Japan's national convention, 30 percent of the papers were AI related. Fujitsu has a scheduling system for computers which will be used with a total of 140 CPU's and peripherals for software development in Fujitsu's Numazu Works. Mitsubishi Electric has announced an expert sytem for making estimates of machinery products NEC says it will use TMS or dependency-directed backtracking in its PECE system and it will be used in diagnosis. __________________________________________________________________________ Other: Tecknowledge announced revenue of 4 million and income of $180 thousand for third fiscal quarter. Symbolics has released version 7.0 of its LISP software. Kurzweill has raised seven million in its third round of venture capital. IBM has announced an expert system environment for MVS which is similar to their product running under VM. Battelle is developing a natural language interface for databases which is independent of domain and DBMS. It runs on a Xerox LISP machine and interfaces with a DBMS on a mainframe. They also have a package for PC's which links with a mainframe and is available in French and German Digitalk's Smalltalk environment, Methods, now can communicate with remote UNIX computers. A toolkit for design of voice or telephone application packages which interfaces with TI-Speech technology, has been announced by Denniston. Intermetrics is beta testing its Common LISP 370 for IBM mainframes. It includes interfaces with C and Fortran. A District Court found that ArtellIgence's OPS5+ product was developed by Computer Thought employees during their employment with Computer Thought. Compuater Thought has a Judgement and permanent injunction against ArtellIgence. MIT has started a project to explore the relationship between symbolic and numeric computing, called Mixed Computing. ------------------------------ Date: Fri 23 May 86 14:09:08-PDT From: C.S./Math Library Subject: Math/CS Library--New Journal-International Journal of Intelligent Systems [Forwarded from the Stanford bboard by Laws@SRI-AI.] We have just received volume 1, number 1, spring 1986 of the International Journal of Intelligent Systems. Ronald R. Yager is the editor and it is published by John Wiley and Sons. The editorial board include the following people: Hans Berliner, Ronald Brachman, Richard Duda, Marvin Minsky, Judea Pearl, Dimitri Poselov, Azriel Rosenfeld, Lotfi Zadeh, Jin Wen Zhang, and Hans Zimmerman along with others. The following articles are included in the first issue: Constructs And Phenomena Common To The Semantically- Rich Domains by Beth Adelson; An Intelligent Computer Vision System by Su-shing Chen; Hierarchical Representation Of Problem-Solving Knowledge In A Frame-Based Process Planning System by Dana S. Nau and Tien-Chien Chang; Toward General Theory of Reasoning With Uncertainty. 1. Nonspecificity and Fuzziness by Ronald R. Yager; and Review of Heuristics-Intelligent Strategies for Computer Problem Solving by Judea Pearl, Henri Farreny, and Henri Prade. Manuscripts should be submitted to the editor, Dr. Ronald R. Yager, International Journal of Intelligent Systems, Machine Intelligence Institute, Iona College, New Rochelle, New York 10801. The journal will be published quarterly and will keep a balance between the theoretical and applied, as well as provide a venue for experimental work. Harry LLull ------------------------------ Date: 29 Apr 1986 18:51-EDT From: VERACSD@USC-ISI.ARPA Subject: Benchmarking KBES-Tools [Forwarded from the Prolog Digest by Laws@SRI-AI.] I have come across some recent benchmarks from NASA (U.S. Gov't MEMORANDUM from the FM7/AI Section, April 3, 1986) which compared various KBES tools' (ART, OP, KEE & CLIPS) times for solving the MONKEY-AND-BANANA problem. (This toy problem is explained in detail along with OPS source in Brownston et. al.'s "Programming Expert Systems in OPS5".) Although the benchmarks include backward-chaining solutions to the problem in both KEE and ART (along with forward chaining counterparts), there is no PROLOG implementation in the comparison. I am very interested in a PROLOG comparison, and am in the process of implementing one. Unfortunately, I am not (yet) a competent PROLOG programmer and am currently learning my way around PROLOG on a DEC-20. Consequently, any advice/suggestions re implementing this benchmark and timing it effectively would be be useful & appreciated. (By the way, the time to beat is 1.2 secs. for a forward-chaining implementation using ART on a 3640 with 4MB main-memory.) I would be glad to share the results with anyone who offers assistance. (Or for that matter with whomever is interested.) ------------------------------ Date: Tue, 27 May 1986 20:52 EDT From: Dr. Alex Bykat Subject: Re: Abstracts of Technical Talks Published on AI-LIST In AIList V4 #120 Peter R.Spool writes: >Date: 9 May 86 10:24:22 EDT >From: PRSPOOL@RED.RUTGERS.EDU >Subject: Abstracts of Technical Talks Published on AI-LIST > > None of us surely, can attend all of the talks announced via the >AI-LIST. The abstracts which appear have served as a useful pointer for >me to current research in many different areas. I trust this has been >true for many of you as well. These abstracts could serve this secondary >purpose even better, if those people who post these abstracts to the >network, made an effort to include two addtional pieces of information >in them: > 1) A Computer Network address of the speaker. > 2) One or more references to any recently published material > with the same, or similar content to the talk. >I know that this information would help me enormously. I assume the >same is true of others. > Let me echo Peter's request. On a number of occasions I had to bother the speakers' hosts requesting precisely that kind of information. While many of the hosts respond graciously and promptly, no doubt they are busy enough without fending off such requests. A. Bykat Center of Excellence - Computer Applications University of Tennessee Chattanooga, TN 37402 Acknowledge-To: Dr. Alex Bykat [Unfortunately, the people who compose these seminar notices seldom read AIList. Those of you who wish to influence the notice formats should contact the authors directly. -- KIL] ------------------------------ Date: Mon 26 May 86 14:57:24-PDT From: Stuart Russell Subject: Seminar - Analogical and Inductive Reasoning (SU) PhD Orals Announcement Analogical and Inductive Reasoning Stuart J. Russell Department of Computer Science Stanford University Tuesday June 3rd 9.15 a.m. Building 370 Room 370 I show the need for the application of domain knowledge in analogical reasoning, and propose that this knowledge must take the form of a new class of rule called a "determination". By giving determinations a first-order definition, they can be used to make valid analogical inferences; I have thus been able to implement determination-based analogical reasoning as part of the MRS logic programming system. In such a system, analogical reasoning can be more efficient than rule-based reasoning for some tasks. Determinations appear to be a common form of regularity in the world, and form a natural stage in the acquisition of knowledge. My approach to the study of analogy can be extended to the general problem of the use of knowledge in induction, leading to the beginning of a domain-independent theory of inductive reasoning. If time permits, I will also show how the concept of determinations leads to a justification and quantitative analysis of analogy by similarity. ------------------------------ Date: Tue 27 May 86 14:56:47-PDT From: Christine Pasley Subject: Seminar - Reasoning about Semiconductor Fabrication (SU) CS529 - AI In Design & Manufacturing Instructor: Dr. J. M. Tenenbaum Title: Modeling and Reasoning about Semiconductor Fabrication Speakers: John Mohammed and Michael Klein From: Schlumberger Palo Alto Research and Shiva Multisystems Date: Wednesday, May 28, 1986 Time: 4:00 - 5:30 Place: Terman 556 Abstract for John Mohammed's talk: As part of a larger effort aimed at providing symbolic, computer-aided tools for semiconductor fabrication experts, we have developed qualitative models of the operations performed during semiconductor manufacture. By qualitativiely simulating a sequence of these models we generate a description of how a wafer is affected by the operations. This description encodes the entire history of processing for the wafer and causally relates the attributes that describe the structures on the wafer to the processing operations responsible for creating those structures. These causal relationships can be used to support many reasoning tasks in the semiconductor fabrication domain, including synthesis of new recipes, and diagnosis of failures in operating fabrication lines. Abstract for Michael Klein's talk: Current integrated circuit (IC) process computer-aided design (CAD) tools are most useful in verifying or tuning IC processes in the vicinity of an acceptable solution. However, these highly compute-intensive tools are often used too early and too often in the design cycle. Cameo, an expert CAD system, assists IC process designers in synthesizing photolithography step descriptions before using other CAD tools. Cameo has a modular knowledge base containing knowledge for all levels of the synthesis process, including heuristic knowledge as well as algorithms, formulas, graphs, and tables. It supports the parallel development of numerous design alternatives in an efficient manner and links to existing CAD tools such as IC process simulators. Visitors welcome! ------------------------------ Date: Tue, 27 May 86 17:52:01 pdt From: Vaughan Pratt Subject: Seminar - Levels of Knowledge in Distributed Computing (SU) Speaker: Rohit Parikh Date: Thursday, June 5, 1986 Time: 9:30-10:45 Place: MJ352 Title: Levels of Knowledge in Distributed Computing Abstract: It is well known that the notion of knowledge is a useful one for understanding distributed computing and in particular, synchronous and asynchronous communication can be distinguished by the possibility or impossibility of common knowledge being achieved. We show that knowledge of facts in distributed systems can be at various levels, these levels are partially ordered, and that a characterisation of these levels can be given which brings together knowledge, regular sets and well partial orderings (not the same as well founded partial orderings). ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Fri May 30 18:39:26 1986 Date: Fri, 30 May 86 18:39:21 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #134 Status: R AIList Digest Friday, 30 May 1986 Volume 4 : Issue 134 Today's Topics: Query - MIT Research on Symbolic/Numeric Processing, AI Tools - Functional Programming and AI & Common LISP Style, References - Neural Networks & Lenat's AM, Linguistics - 'Xerox' vs. 'xerox', Psychology - Doing AI Backwards & Learning ---------------------------------------------------------------------- Date: Wed, 28 May 86 14:34:04 PDT From: SERAFINI%FAE@ames-io.ARPA Subject: MIT research on symbolic/numeric processing >>AIList Digest Volume 4 : Issue 133 >>From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU >>Subject: Spang Robinson Report, Volume 2 No. 5 >>MIT has started a project to explore the relationship >>between symbolic and numeric computing, called Mixed Computing. Does anybody have more info about this project? Reply to serafini%far@ames-io.ARPA Thanks. ------------------------------ Date: 29 May 86 11:32:00 edt From: Walter Hamscher Subject: Functional programming and AI Date: 21 May 86 13:14:00 EST From: "CUGINI, JOHN" Reply-to: "CUGINI, JOHN" Do working AI programs really exploit these features a lot? Eg, do "learning" programs construct unforeseen rules, perhaps based on generalization from examples, and then use the rules? Or is functional programming just a trick that happens to be easy to implement in an interpreted language? I think this is a slightly odd characterization of `functional programming.' Maybe I'm confused, but I always thought a `functional language' meant (in a nutshell) that there are no side effects. In contrast, the one important `side effect' you're talking about here is constructing a function at runtime and squirreling it away in a knowledge base, to be run later. In theory you could do the squirreling by passing around the whole state of the world and non-destructively modifying that datastucture as you go, but that's orthogonal to what you seem to be talking about (besides being painful). Whatever it's called -- this indistinguishability between code and data -- it's true that it's a ``trick,'' but I think it's an important one. In fact as I think about it now, every AI program I've ever seen _at_some_point_ passes functions around, sticks them in places like on property lists as demons, and/or mashes together portions of bodies of different functions and sticks the resulting lambda-expression somewhere to run later (Well, maybe Mycin didn't (but Teiresias did)). As far as learning programs that construct functions, it's all in the eyes of the interpreter. A rule that is going to be run by a rule interpreter counts as a kind of function (it's just not necessarily in LISP per se). So, since Tom Mitchell's LEX (for example) builds and modifies the bodies of heuristic rules which later get applied to the integration problem, it falls in this category. Tom Diettrich's EG does something like this too. I'm sure there are jillions of other examples but I'm not that deep into machine learning. And of course there's always AM (which by now should be familiar to all readers of AiList) which (among other things) did random structure modifications to LISP functions, then ran them to see what they did. For example, it might start with the following definition of EQUAL: (defun EQUAL (a b) (cond ((eq a b) t) ((and (consp a) (consp b)) (and (EQUAL (car a) (car b)) (EQUAL (cdr a) (cdr b)))) (t nil))) To generalize the function, it drops one of the conjunctions and changes its name (including the recursive call): (defun SOME-NEW-FUNCTION (a b) (cond ((eq a b) t) ((and (consp a) (consp b)) (SOME-NEW-FUNCTION (cdr a) (cdr b))) (t nil))) Lo and behold, SOME-NEW-FUNCTION is a new predicate meaning something like "same length list." So there's an existence proof at least. Walter Hamscher ------------------------------ Date: 15 May 86 17:42:18 GMT From: tektronix!uw-beaver!ssc-vax!bcsaic!michaelm@ucbvax.berkeley.edu (michael maxwell) Subject: Re: Common LISP style standards. In article <3787@utah-cs.UUCP> shebs@utah-cs.UUCP (Stanley Shebs) writes: >Sequence functions and mapping functions are generally preferable to >handwritten loops, since the Lisp wizards will probably have spent >a lot of time making them both efficient and correct (watch out though; >quality varies from implementation to implementation). I'm in a little different boat, since we're using Franz rather than Common Lisp, so perhaps the issues are a bit different when you're using Monster, I mean Common, Lisp... so at the risk of rushing in where angels etc.: A common situation we find ourselves in is the following. We have a long list, and we wish to apply some test to each member of the list. However, at some point in the list, if the test returns a certain value, there is no need to look further: we can jump out of processing the list right there, and thus save time. Now you can jump out of a do loop with "(return )", but you can't jump out of a mapc (mapcar etc.) with "return." So we wind up using "do" a lot of places where it would otherwise be natural to use "mapcar". I suppose I could use "catch" and "throw", but that looks so much like "goto" that I feel sinful if I use that solution... Any style suggestions? -- Mike Maxwell Boeing Artificial Intelligence Center ...uw-beaver!uw-june!bcsaic!michaelm ------------------------------ Date: 27 May 86 21:37:58 GMT From: ulysses!mhuxr!mhuxn!mhuxm!mhuxf!mhuxi!mhuhk!mhuxt!houxm!mtuxo!mtfmt !brian@ucbvax.berkeley.edu (B.CASTLE) Subject: Neural Networks For those interested in some historical references on neural network function, the following may be of interest : Dynamics: NUNEZ, P.L. (1981). ELECTRIC FIELDS OF THE BRAIN. The Neurophysics of EEG. Oxford University Press, NY. This book contains a pretty good overview of EEG, and also contains an interesting model of brain dynamics based on neural network connectivity. Learning: OJA, E. (1983). SUBSPACE METHODS OF PATTERN RECOGNITION. Research Studies Press, Ltd. Letchworth, Hertfordshire, England. (John Wiley and Sons, Inc., New York.) (For those with a PR background, and those having read and understood Kohonen). KOHONEN, T. (1977) - ASSOCIATIVE MEMORY. A System-Theoretical Approach. Springer-Verlag, Berlin. (1980) - CONTENT ADDRESSABLE MEMORIES. Springer- Verlag, Berlin. (1984) - SELF-ORGANIZATION AND ASSOCIATIVE MEMORY. Springer Series in Info. Sci. 8. Springer-Verlag, New York. These works provide a basic introduction to the nature of CAM systems (frame-based only), and the basic philosophy of self-organization in such systems. SUTTON, R.S. and A.G. BARTO (1981). "Toward A Modern Theory of Adaptive Networks: Expectation and Prediction." Psychological Review 88(2):135. This article provides an overview of the 'tuning' of synaptic parameters in self-organizing systems, and a reasonable bibliography. Classic: MINSKY, M. and S. PAPERT (1968). PERCEPTRONS. An Introduction to Computational Geometry. MIT Press, Cambridge, MA. This book should be read by all neural network enthusiasts. In a historical context, the Hopfield model is important insofar as it uses Monte Carlo methods to generate the network behavior. There are many other synchronous and asynchronous neural network models in the literature on neuroscience, biophysics, and cognitive psychology, as well as computer and electrical engineering. I have amassed a list of over a hundred books and articles, which I will be glad to distribute, if anyone is interested. However, keep in mind that the connection machines and chips are still very far from approaching neural networks in functional capability and diversity. brian castle @ att (MT 2D-217 middletown, nj, 07748) (...!allegra!orion!brian) (...!allegra!mtfmt!brian) ------------------------------ Date: Thu, 29 May 1986 01:07 EDT From: "David D. Story" Subject: Need Ref for "Automated Mathematician" by Doug Lenat Discussion of "Automated Mathematician" His thesis was in "Knowledge Based Systems on Artful Dumbness" - McGraw-Hill - 1982 ISBN 0-07-015557-7. Wrong again...Oh well, try this one. The price is 20 odd bucks. Sorry. I called it Artful Dumbness cause it had to rediscover primes. In fact it is quite a study - Does anyone have source? Working Papers are not referenced in the thesis so the searcher is on his own. I'm sure they must exist someplace. Nice bibliography in the back of the Thesis. ------------------------------ Date: Thu, 8 May 86 21:01:58 cdt From: ihnp4!uiucdcs!ccvaxa!aglew@seismo.CSS.GOV (Andy Glew) Subject: 'Xerox' vs. 'xerox'? >It's interesting to note that at one time, "frigidaire" (no caps) was >considered to be a synonym for "refrigerator." Frigidaire, the >company, fought this in order not to lose trademark status. How often >does one hear this usage these days? > >Rich Alderson >Alderson@Score.Stanford.EDU (=SU-SCORE.ARPA) Do you speak French? Could common usage in another language lead to the loss of trademark status? Andy "Krazy" Glew. Gould CSD-Urbana. USEnet: ihnp4!uiucdcs!ccvaxa!aglew 1101 E. University, Urbana, IL 61801 ARPAnet: aglew@gswd-vms ------------------------------ Date: 29 May 86 10:55:41 edt From: Walter Hamscher Subject: Doing AI backwards (from machine to man) Date: 18 May 86 05:39:39 GMT From: ernie.Berkeley.EDU!tedrick@ucbvax.berkeley.edu (Tom Tedrick) More on Barry Kort's "Problem of the right-hand tail" (ie social persecution of those with high intelligence). My heart bleeds for those unfortunate people on the right-hand tail. How about a Take a Genius to Lunch Week. Maybe we could get some rock stars to do a ``Brain Aid.'' I take it this problem is distinct from the ``problem of the left-hand tail'' and the ``problem of the right-hand tail against the big hump in the middle''. (* * *) Thus we see again how women have a brilliant gift for asking seemingly innocent favors which are really enormously costly. The subtle nature of the problem makes it difficult to pin down the real poison in their approach. And it's a good thing you pointed this out. We men better watch out for those seemingly innocent favors, *especially* from women! Hmm, poison, you say... Speaking of favors, please do us all a favor; keep your grim and pathetic misogyny to yourself. Or send your ravings to bandykin. (* * *) I am studying how machines function in order to find better ways for humans to function. Why not study how machines live in order to find better ways for humans to live. Or how machines laugh in order to find better ways for humans to laugh. Or how machines get over their insecurities in order to find better ways for humans to get over their insecurities. (* * *) (Since it is only recently that the need for rigorous treatment of models of computation has induced us to really make some progress in understanding these things.) Yes, I'm sure there there's a `cybernetic' explanation for all of this. Walter Hamscher ------------------------------ Date: 9 May 86 05:02:09 GMT From: ihnp4!ltuxa!ttrdc!levy@ucbvax.berkeley.edu (Daniel R. Levy) Subject: Re: "The Knowledge" In article <5500032@uiucdcsb>, schraith@uiucdcsb.CS.UIUC.EDU writes: > It seems to me that if AI researchers wish to build a system which > has any versatility, it will have to be able to learn, probably > in a similar manner to the taxicab drivers. Bierre states this problem: > "Organize a symbolic recording of an ongoing stream of fly-by > sensory data, on the fly, such that at any given time as much as > possible can be quickly remembered of the entire stream." > Surely computer professionals have better things to do, ultimately, > than spoonfeed all the knowledge to a computer it will ever need. As nothing but an interested observer in this discussion (I am in no wise an AI guru, so please forgive me if I bumble) your observation indeed makes sense me, that an A.I. system could well do better by "learning" than by having all its "smarts" hardcoded in beforehand. But it also seems possible that once a computer system HAS been "trained" in this way, it should be quite easy to mass produce as many equally capable copies of that system as desired; just dump its "memory" and reload it on other systems. Any comments? Does a "learning" system (or one that knows how to teach itself) indeed hold more promise than distilling expert human knowledge and hardcoding it in? Perhaps I've answered my own question, that the system that can "learn" is better able to adapt to new developments in the area it is supposed to be "intelligent" in than one which is static. Maybe the best of both worlds could apply (the distilled human knowledge coded in as a solid base, but the system is free to expand on that base as it "learns" more and more)? -- ------------------------------- Disclaimer: The views contained herein are | dan levy | yvel nad | my own and are not at all those of my em- | an engihacker @ | ployer or the administrator of any computer | at&t computer systems division | upon which I may hack. | skokie, illinois | -------------------------------- Path: ..!{akgua,homxb,ihnp4,ltuxa,mvuxa, vax135}!ttrdc!levy ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 3 06:54:34 1986 Date: Tue, 3 Jun 86 06:54:28 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #135 Status: R AIList Digest Tuesday, 3 Jun 1986 Volume 4 : Issue 135 Today's Topics: Queries - OPS5 in PSL & Dempster-Shafer Scoring Rules & Formal Definition of Lisp Systems & Lazy Evaluation, Techniques - Common Lisp style ---------------------------------------------------------------------- Date: 29 May 86 19:05:27 GMT From: mcvax!botter!klipper!fons@seismo (Fons Botman) Subject: OPS5 in PSL request I am looking for an OPS5 implementation in PSL. Please mail any pointers or source to: Kievit@Hlerul5.Bitnet For a friend Fons Botman fons@vu44.UUCP ------------------------------ Date: 30 May 86 01:33:15 GMT From: kaist!cskaist!mgchung@seismo ([Mingyo Chung]) Subject: Search for scoring rules paper! To. everyone who can give me a help...... I have broadcast this message for asking a favor. "Interval (or Range) Extension of Reproducing-Scoring-Rule by Dempster and Shafer's Rule" is my Master thesis. Thus, I seek for papers on "scoring rules" and have found out a paper that seems to be related with "scoring rules".By the way, that paper is not found in Korea.That paper is as follows :: Lindley, D.V. (1982),"Scoring rules and the inevitability of probability", International Statistics Review,vol 50, 1-26 Do you have this paper ? Then, would you mind giving me a help ? Would you please send me a copy of it ? You can contact me through electronic mail [Path:mgchung%cskaist%kaist.csnet@CSNET-RELAY] [Address: Mingyo Chung Dept. of Computer Science KAIST P.O Box 150 CheongRyang Seoul Korea 131 ] I'll be waiting for a good response .... Sincerely Yours. ------------------------------ Date: 5 Jun 86 20:03:44 GMT From: allegra!mit-eddie!think!caip!seismo!mcvax!euroies!rreilly@ucbvax .berkeley.edu (Dr Ronan Reilly) Subject: Formal definition of Lisp systems Does anyone have references to a system which could be used to formally define large Lisp program suites? What I have in mind is something akin to the dataflow system for procedural languages. Thanks in advance, Ronan ------------------------------ Date: Mon, 2 Jun 86 09:27 N From: DESMEDT%HNYKUN52.BITNET@WISCVM.WISC.EDU Subject: Lisp & lazy evaluation In AIList Digest V4 #134, Mike Maxwell reluctantly prefers the efficiency of a hand-coded "do" construction in Lisp, although mapping a function on a list would be more elegant. Indeed, mapping sometimes causes many unnecessary computations. Consider the following example: (defun member (element list) (apply 'or (mapcar #'(lambda (list-element) (eql element list-element)) list))) One solution to prevent wasteful computation is a "lazy" evaluation mechanism, which computes only as much as is needed by other computations. For example, the mapping in the above example would be performed only up to the point where "or" finds a non-nil value and doesn't want to evaluate any more arguments. Anyway, I don't really want to lecture here, but I want to ask a question: has anyone out there experimented with lazy evaluation in a Lisp system? Are any working systems (or prototypes) available? Any good references to the literature? Koenraad de Smedt desmedt@hnykun52.bitnet ------------------------------ Date: 29 May 86 15:20:04 GMT From: allegra!princeton!caip!seismo!ut-sally!utah-cs!shebs@ucbvax.berkeley .edu (Stanley Shebs) Subject: Re: Common LISP style standards. In article <545@bcsaic.UUCP> michaelm@bcsaic.UUCP (michael maxwell) writes: >I'm in a little different boat, since we're using Franz rather than Common >Lisp I remember Franz (vaguely)... :-) >A common situation we find ourselves in is the following. We have a list, >and we wish to apply some test to each member of the list. However, at some >point in the list, if the test returns a certain value, there is no need to >look further: we can jump out of processing the list right there, and thus >save time. Common Lisp provides "some", "every", "notany", and "notevery" functions which all do variations of what you're asking for. They take a predicate and one or more sequences as arguments, and apply the predicate to each element in the sequence, and may stop in the middle. The behavior is sufficiently specified for you to use side effects in the predicate. BTW, if these four functions weren't around, Common Lisp would be smaller. >I suppose I could use "catch" and "throw", but that looks so much like "goto" >that I feel sinful if I use that solution... "Sinfulness" is a silly concept that quite a few folks in the computer community have gotten into - a sort of aftereffect of structured programming. The *real* reason for using higher-level constructs is efficiency, both in programmer and execution time. stan shebs utah-cs!shebs ------------------------------ Date: Sat, 31 May 1986 11:23 EDT From: "Scott E. Fahlman" Subject: Common Lisp style A common situation we find ourselves in is the following. We have a long list, and we wish to apply some test to each member of the list. ... Any style suggestions? Well, if you were using "Monster, I mean Common, Lisp..." there would be a built-in function to handle this case. If I understand correctly what you are asking for, the function is FIND-IF. Our attempt to meet various needs like this is why the language is big. You can't have it both ways. In a Lisp without a built-in solution, the right answer is probably to create your own FIND-IF macro and use it for this case. It creates the same DO-loop you would have to write, but is much less confusing for the casual reader and less prone to errors once you get the macro right. If you find yourself wrestling with a variety of such problems, there are several iteration packages available that provide a somewhat perspicuous syntax for the user and that create efficient DO loops of various kinds. Your Franz Lisp vendor can probably point you to a version of the LOOP facility that will run on your system. Something of this sort will probably find its way into standard Common Lisp eventually, but we are having a hard time deciding on a syntax that we all can live with. -- Scott ------------------------------ Date: 1-Jun-86 14:52:27 From: Dan Cerys Subject: Re: Common LISP style standards Date: 15 May 86 17:42:18 GMT From: tektronix!uw-beaver!ssc-vax!bcsaic!michaelm@ucbvax.berkeley.edu (michael maxwell) A common situation we find ourselves in is the following. We have a long list, and we wish to apply some test to each member of the list. ... It sounds like the function you want is MEMBER-IF. This takes two required arguments, a predicate and a list. As soon as the predicate succeeds on one of the elements of the list, the tail of the list is returned, else NIL is returned. There is nothing wrong with using DO or any of the mapping functions, as long as you are using the "best" function for the task. In the case you've described, MEMBER-IF is perfect because it immediately conveys to the reader (which may be yourself months after you've written it) what is being tested for. DOs and RETURNs can hide this meaning. Another useful variant of DO is DOLIST, which is similar (and prefered by many) to MAPC. Within our group, we prefer to use the mapping functions only where they appear to be "natural" to the task (eg, list transformations). But granted, what is "best" and "natural" depends a lot on your background and approach to Lisp. ------------------------------ Date: 30 May 86 17:05:44 GMT From: decvax!cca!lmi-angel!rpk@ucbvax.berkeley.edu (Bob Krajewski) Subject: Re: Common LISP style standards. In article <> michaelm@bcsaic.UUCP (michael maxwell) writes: >In article <3787@utah-cs.UUCP> shebs@utah-cs.UUCP (Stanley Shebs) writes: >>Sequence functions and mapping functions are generally preferable to >>handwritten loops, since the Lisp wizards will probably have spent >>a lot of time making them both efficient and correct (watch out though; >>quality varies from implementation to implementation). This is very true. It will be interesting to see how Lisp compiler technology meets the challenge... >A common situation we find ourselves in is the following. ... There are two Common Lispy ways doing this. The first is the use the function (SOME predicate sequence &rest more-sequences), which returns the first non-NIL result of the application of the predicate to the each set of elements of the sequences (like map). Since this is a generic sequence function that can take either vectors or lists, you'll probably want to write something like (some #'(lambda (x) (when (wonderful-p (sibling x)) (father x))) (the list a-list)) A good compiler would do two things here: it would first notice that the only sequence is a list. Thus, the ``stepping'' function for the sequence type (CDR, and CAR for element selection) is known in advance. And since that is so, it can open code the loop, thus generating a DO-like thing that you would have otherwise written by hand. Another way is to use CATCH and THROW. When the THROW is lexically visible from the CATCH, very good code can be generated in certain cases. As for whether it's icky or not, at least CATCH establishes a lexical scope for where the ``goto'' is valid, when the THROW is visible. -- Robert P. Krajewski Internet/MIT: RPK@MC.LCS.MIT.EDU UUCP: ...{cca,harvard,mit-eddie}!lmi-angel!rpk ------------------------------ Date: 1 Jun 86 17:03:30 GMT From: allegra!princeton!caip!topaz!harvard!bu-cs!bzs@ucbvax.berkeley.edu (Barry Shein) Subject: Re: Common LISP style standards. [re: Franz Lisp] >Now you can jump out of a do loop with "(return )", but you >can't jump out of a mapc (mapcar etc.) with "return." So we wind up using >"do" a lot of places where it would otherwise be natural to use "mapcar". I >suppose I could use "catch" and "throw", but that looks so much like "goto" >that I feel sinful if I use that solution... >Mike Maxwell >Boeing Artificial Intelligence Center Howsabout: (defun foo (x) (prog nil (mapc '(lambda (y) (cond ((null y) (return 'DONE)) (t (print y)))) x))) try for example (foo '(a b nil c d)) -Barry Shein, Boston University ------------------------------ Date: 2 Jun 86 17:10:26 GMT From: hplabs!hplabsc!dsmith@ucbvax.berkeley.edu (David Smith) Subject: Re: Common LISP style standards. > In article <3787@utah-cs.UUCP> shebs@utah-cs.UUCP (Stanley Shebs) writes: > >Sequence functions and mapping functions are generally preferable to > >handwritten loops, ... > I'm in a little different boat, since we're using Franz rather than Common > Lisp, so perhaps the issues are a bit different ... > Mike Maxwell CMU incorporated functions of CMUlisp into Franz, and these are apparently shipped with Franz: at least, on my computer, they are in /usr/src/ucb/lisp/lisplib/cmufncs.l. One of these functions is the function some. (some 'mylist 'func1 'func2) returns the first tail of mylist for which func1 of its car returns a non-nil value. Otherwise nil is returned. Successive tails of mylist are obtained by repeated application of func2 (usually cdr, or nil, which implies cdr). A nice cover macro for this is "exists". Example: (exists i '(2 5 3 8 4 1) (> i 6)) returns (8 4 1). David Smith HP Labs ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 3 06:54:48 1986 Date: Tue, 3 Jun 86 06:54:42 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #136 Status: R AIList Digest Tuesday, 3 Jun 1986 Volume 4 : Issue 136 Today's Topics: Conferences - DOD Decsion Aiding (Man-Machine Interfaces) & SLP '86 Program and Tutorial Abstracts ---------------------------------------------------------------------- Date: 30 May 86 10:03:00 EDT From: "MATHER, MICHAEL" Reply-to: "MATHER, MICHAEL" Subject: Conference - DOD DECSION AIDING CONF, CALL FOR PAPERS ON MMI FOURTH ANNUAL WORKSHOP ON COMMAND AND CONTROL DECISION AIDING NOVEMBER 4-6, 1986 US AIR FORCE MUSEUM AUDITORIUM WRIGHT-PATTERSON AFB DAYTON, OH As is stated in the name of the conference, the workshop will address decision aiding in military command and control systems. U.S. citizenship and at least a Secret clearance are required for attendance. Sessions will be presented in the following areas: I. Requirements II. Technology III. Man-Machine Interface IV. Test and Evaluation V. Training Systems VI. Applications There will also be a Round Table discussion at the end of the conference. I am the Chair for the session on Man-Machine Interface. Anyone working on a Man-Machine Interface project related to command and control, intelligence, decision aiding, etc. and interested in presenting a paper at the conference is urged to contact me as soon as possible. I must make a decision on papers to be presented by 15 Aug 86. CPT Mike Mather US Army Research Institute ATTN: PERI-SF 5001 Eisenhower Ave. Alexandria, VA 22333-5600 Phone: (202) 274-5477/5482 (AVN) 284-5477/5482 DDN: MATHER@ARI-HQ1 ------------------------------ Date: Wed, 28 May 86 15:47:12 MDT From: keller@utah-cs.ARPA (Bob Keller) Subject: Conference - SLP '86 Program and Tutorial Abstracts [Note: this is not the same as the 3rd Int. Conf. on Logic Programming, London, July 14-18, that was announced in V4 #113. -- KIL] SCHEDULE SLP '86 Third IEEE Symposium on LOGIC PROGRAMMING September 21-25, 1986 Westin Hotel Utah Salt Lake City, Utah Conference Chairperson Gary Lindstrom, University of Utah Program Chairperson Local Arrangements Chairperson Robert M. Keller, University of Utah Thomas C. Henderson, University of Utah Tutorials Chairperson Exhibits Chairperson George Luger, University of New Mexico Ross Overbeek, Argonne National Lab. Program Committee Francois Bancilhon, MCC William Kornfeld, Quintus Systems John Conery, University of Oregon Gary Lindstrom, University of Utah Al Despain, U.C. Berkeley George Luger, University of New Mexico Herve Gallaire, ECRC, Munich Rikio Onai, ICOT/NTT, Tokyo Seif Haridi, SICS, Stockholm Ross Overbeek, Argonne National Lab. Lynette Hirschman, SDC Mark Stickel, SRI International Peter Kogge, IBM, Owego Sten Ake Tarnlund, Uppsala University SUNDAY, September 21 19:00 - 22:00 Symposium and tutorial registration MONDAY, September 22 08:00 - 09:00 Symposium and tutorial registration 09:00 - 17:30 TUTORIALS (concurrent) Please see attached abstracts. George Luger Introduction to AI Programming in Prolog University of New Mexico David Scott Warren Building Prolog Interpreters SUNY, Stony Brook Neil Ostlund Theory of Parallelism, with Applications to Romas Aleliunas Logic Programming University of Waterloo 12:00 - 17:30 Exhibit set up time 18:00 - 22:00 Symposium registration 20:00 - 22:00 Reception TUESDAY, September 23 08:00 - 12:30 Symposium registration 09:00 Exhibits open 09:00 - 09:30 Welcome and announcements 09:30 - 10:30 INVITED SPEAKER: W. W. Bledsoe Some Thoughts on Proof Discovery 11:00 - 12:30 SESSION 1: Applications The Logic of Tensed Statements in English - an Application of Logic Programming Peter Ohrstrom, University of Aalborg Nils Klarlund, University of Aarhus Incremental Flavor-Mixing of Meta-Interpreters for Expert System Construction Leon Sterling and Randall D. Beer Case Western Reserve University The Phoning Philosopher's Problem or Logic Programming for Telecommunications Applications J.L. Armstrong, N.A. Elshiewy, and R. Virding Ericsson Telecom 14:00 - 15:30 SESSION 2: Secondary Storage EDUCE - A Marriage of Convenience: Prolog and a Relational DBMS Jorge Bocca, ECRC, Munich Paging Strategy for Prolog Based Dynamic Virtual Memory Mark Ross, Royal Melbourne Institute of Technology K. Ramamohanarao, University of Melbourne A Logical Treatment of Secondary Storage Anthony J. Kusalik, University of Saskatchewan Ian T. Foster, Imperial College, London 16:00 - 17:30 SESSION 3: Compilation Compiling Control Maurice Bruynooghe, Danny De Schreye, Bruno Krekels Katholieke Universiteit Leuven Automatic Mode Inference for Prolog Programs Saumya K. Debray, David S. Warren SUNY at Stony Brook IDEAL: an Ideal DEductive Applicative Language Pier Giorgio Bosco, Elio Giovannetti C.S.E.L.T., Torino 17:30 - 19:30 Reception 20:30 - 22:30 Panel (Wm. Kornfeld, moderator) Logic Programming for Systems Programming WEDNESDAY, September 24 09:00 - 10:00 INVITED SPEAKER: Sten Ake Tarnlund Logic Programming - A Logical View 10:30 - 12:00 SESSION 4: Theory A Theory of Modules for Logic Programming Dale Miller University of Pennsylvania Building-In Classical Equality into Prolog P. Hoddinott, E.W. Elcock The University of Western Ontario Negation as Failure Using Tight Derivations for General Logic Programs Allen Van Gelder Stanford University 13:30 - 15:00 SESSION 5: Control Characterisation of Terminating Logic Programs Thomas Vasak, The University of New South Wales John Potter, New South Wales Institute of Technology An Execution Model for Committed-Choice Non-Deterministic Languages Jim Crammond Heriot-Watt University Timestamped Term Representation in Implementing Prolog Heikki Mannila, Esko Ukkonen University of Helsinki 15:30 - 22:00 Excursion THURSDAY, September 25 09:00 - 10:30 SESSION 6: Unification Refutation Methods for Horn Clauses with Equality Based on E-Unification Jean H. Gallier and Stan Raatz University of Pennsylvania An Algorithm for Unification in Equational Theories Alberto Martelli, Gianfranco Rossi Universita' di Torino An Implementation of Narrowing: the RITE Way Alan Josephson and Nachum Dershowitz University of Illinois at Urbana-Champaign 11:00 - 12:30 SESSION 7: Parallelism Selecting the Backtrack Literal in the AND Process of the AND/OR Process Model Nam S. Woo and Kwang-Moo Choe AT & T Bell Laboratories Distributed Semi-Intelligent Backtracking for a Stack-based AND-parallel Prolog Peter Borgwardt, Tektronix Labs Doris Rea, University of Minnesota The Sync Model for Parallel Execution of Logic Programming Pey-yun Peggy Li and Alain J. Martin California Institute of Technology 14:00 - 15:30 SESSION 8: Performance Redundancy in Function-Free Recursive Rules Jeff Naughton Stanford University Performance Evaluation of a Storage Model for OR-Parallel Execution Andrzej Ciepelewski and Bogumil Hausman Swedish Institute of Computer Science (SICS) MALI: A Memory with a Real-Time Garbage Collector for Implementing Logic Programming Languages Yves Bekkers, Bernard Canet, Olivier Ridoux, Lucien Ungaro IRISA/INRIA Rennes 16:00 - 17:30 SESSION 9: Warren Abstract Machine A High Performance LOW RISC Machine for Logic Programming J.W. Mills Arizona State University Register Allocation in a Prolog Machine Saumya K. Debray SUNY at Stony Brook Garbage Cut for Garbage Collection of Iterative Programs Jonas Barklund and Hakan Millroth Uppsala University EXHIBITS: An exhibit area including displays by publishers, equipment manufacturers, and software houses will accompany the Symposium. The list of exhibitors includes: Arity, Addison-Wesley, Elsevier, Expert Systems, Logicware, Overbeek Enterprises, Prolog Systems, Quintus, and Symbolics. For more information, please contact: Dr. Ross A. Overbeek Mathematics and Computer Science Division Argonne National Laboratory 9700 South Cass Ave. Argonne, IL 60439 312/972-7856 ACCOMODATIONS: The Westin Hotel Utah is a gracious turn of the century hotel with Mobil 4-Star and AAA 5-Star ratings. The Temple Square Hotel, located one city block away, offers basic comforts for budget-conscious attendees. MEALS AND SOCIAL EVENTS: Symposium registrants (excluding students and retired members) will receive tickets for lunches on September 23, 24, and 25, receptions on September 22 and 23, and an excursion the afternoon of September 24. The excursion will comprise a steam train trip through scenic Provo Canyon, and a barbeque at Deer Valley Resort, Park City, Utah. Tutorial registrants will receive lunch tickets for September 22. TRAVEL: The Official Carrier for SLP '86 is United Airlines, and the Official Travel Agent is Morris Travel (361 West Lawndale Drive, Salt Lake City, Utah 84115, phone 1-800-621-3535). Special airfares are available to SLP '86 attendees. Contact Morris Travel for details. A courtesy limousine is available from Salt Lake International Airport to both symposium hotels, running every half hour from 6:30 to 23:00. The taxi fare is approximately $10. CLIMATE: Salt Lake City generally has warm weather in September, although evenings may be cool. Some rain is normal this time of year. SLP '86 Symposium and Tutorial Registration: Advance symposium and tutorial registration is available until September 1, 1986. No refunds will be made after that date. Send a check or money order (no currency will be accepted) payable to "Third IEEE Symposium on Logic Programming" to: Third IEEE Symposium on Logic Programming IEEE Computer Society 1730 Massachusetts Avenue, N.W. Washington, D.C. 20036-1903 Symposium Registration: Advance On-Site IEEE Computer Society members $185 $215 Non-members $230 $270 Full-time student members $ 50 $ 50 Full-time student non-members $ 65 $ 65 Retired members $ 50 $ 50 Tutorial Registration: ("Luger", "Warren", or "Ostlund") Advance On-Site IEEE Computer Society members $140 $170 Non-members $175 $215 SLP '86 Hotel Reservation: Mail or Call: phone 801-531-1000, telex 389434 Westin Hotel Utah Main and South Temple Streets Salt Lake City, UT 84111 A deposit of one night's room or credit card guarantee is required for arrivals after 6pm. Room Rates (circle your choice): Westin Hotel Utah Temple Square Hotel single room $60 $30 double room $70 $36 Reservations must be made mentioning SLP '86 by August 31, 1986 to guarantee these special rates. _______________________________________________________________________________ SLP '86 TUTORIAL ABSTRACTS IMPLEMENTATION OF PROLOG INTERPRETERS AND COMPILERS DAVID SCOTT WARREN SUNY AT STONY BROOK Prolog is by far the most used of various logic programming languages that have been proposed. The reason for this is the existence of very efficient implementations. This tutorial will show in detail how this efficiency is achieved. The first half of this tutorial will concentrate on Prolog compilation. The approach is first to define a Prolog Virtual Machine (PVM), which can be implemented in software, microcode, hardware, or by translation to the language of an existing machine. We will describe in detail the PVM defined by D.H.D. Warren (SRI Technical Note 309) and discuss how its data objects can be represented efficiently. We will also cover issues of compilation of Prolog source programs into efficient PVM programs. ARTIFICIAL INTELLIGENCE AND PROLOG: AN INTRODUCTION TO THEORETICAL ISSUES IN AI WITH PROLOG EXAMPLES GEORGE F. LUGER UNIVERSITY OF NEW MEXICO This tutorial is intended to introduce the important concepts of both Artificial Intelligence and Logic Programming. To accomplish this task, the theoretical issues involved in AI problem solving are presented and discussed. These issues are exemplified with programs written in Prolog that implement the core ideas. Finally, the design of a Prolog interpreter as Resolution Refutation system is presented. The main ideas from AI problem solving that are presented include: 1) An introduction of AI as representation and search. 2) An introduction of the Predicate Calculus as the main representation formalism for Artificial Intelligence. 3) Simple examples of Predicate Calculus representations, including a relational data base. 4) Unification and its role both in Predicate Calculus and Prolog. 5) Recursion, the control mechanism for searching trees and graphs, 6) The design of search strategies, especially depth first, breadth first and best first or "heuristic" techniques, and 7) The Production System and its use both for organizing search in a Prolog data base, as well as the basic data structure for "rule based" Expert Systems. The above topics are presented with simple Prolog program implementations, including a Production System code for demonstrating search strategies. The final topic presented is an analysis of the Prolog interpreter and an analysis of this approach to the more general issue of logic programming. Resolution is considered as an inference strategy and its use in a refutation system for "answer extraction" is presented. More general issues in AI problem solving, such as the relation of "logic" to "functional" programming are also discussed. PARALLELISM IN LOGIC PROGRAMMING NEIL OSTLUND ROMAS ALELIUNAS UNIVERSITY OF WATERLOO The fields of parallel processing and logic programming have independently attracted great interest among computing professionals recently, and there is currently considerable activity at the interface, i.e. in applying the concepts of parallel computing to logic programming and, more specifically yet, to Prolog. The application of parallelism to Logic Programming takes two basic but related directions. The first involves leaving the semantics of sequential programming, say ordinary Prolog, as intact as possible, and uses parallelism, hidden from the programmer, to improve execution speed. This has traditionally been a difficult problem requiring very intelligent compilers. It may be an easier problem with logic programming since parallelism is not artificially made sequential, as with many applications expressed in procedural languages. The second direction involves adding new parallel programming primitives to Logic Programming to allow the programmer to explicitly express the parallelism in an application. This tutorial will assume a basic knowledge of Logic Programming, but will describe current research in parallel computer architectures, and will survey many of the new parallel machines, including shared-memory architectures (RP3, for example) and non-shared-memory architectures (hypercube machines, for example). The tutorial will then describe many of the current proposals for parallelism in Logic Programming, including those that allow the programmer to express the parallelism and those that hide the parallelism from the programmer. Included will be such proposals as Concurrent Prolog, Parlog, Guarded Horn Clauses (GHC), and Delta-Prolog. An attempt will be made to partially evaluate many of these proposals for parallelism in Logic Programming, both from a pragmatic architectural viewpoint as well as from a semantic viewpoint. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 3 06:54:58 1986 Date: Tue, 3 Jun 86 06:54:52 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #137 Status: R AIList Digest Tuesday, 3 Jun 1986 Volume 4 : Issue 137 Today's Topics: Review - Expert Systems Strategies, Psychology - Simulating Insect Behavior, Bindings & AI Tools - Thinking Machine Inc. & Connection Machines ---------------------------------------------------------------------- Date: Wed 28 May 86 11:43:43-CDT From: CMP.BARC@R20.UTEXAS.EDU Subject: Expert Systems Strategies At a recent AI conference, copies of the April 86 issue of the monthly newsletter "Expert Systems Strategies" were being distributed. Almost 14 of the 16 pages dealt with defining "mid-sized tools" and comparing three of them -- M.1, NExpert and Personal Consultant. The overall comparison was informative and I think would provide valuable information to potential buyers of these or any expert system tools. However, there were a number of shortcomings that made me wonder whether the newletter came close to justifying its $20+ price per issue ($247 per year). First, the comparison was at best on a par with those found in PC World, Byte, MacUser, etc. But those magazines give you 75-200 pages of information for $3-4. Of course, they have 75-200 pages of advertising to help keep their prices down. But the ads are useful too, and the absence of advertising in "ES Strategies" has not bought it any apparent degree of independence. The authors of the comparison (Brian Sawyer and Paul Harmon) seem to be very careful not to step very hard on anyone's toes. They point out shortcomings, but in an overly nice fashion. They end up recommending all three products to various markets. (I would be hard-pressed to recommend one, perhaps two, of them to anyone.) Another complaint with "ES Strategies" is the number of errors. The worst of these concerns a small knowledge base, called Beta, that was used to test the features of the various systems. Beta is fully defined, and for each system, a partial representation is shown. Each representation has at least two, and as many as four, errors. Most errors simply give variables the wrong values, while some misname variables or actually misrepresent the knowledge. They also do some confusing representation. E.g., there are two variables, alpha and beta-1, which can take on the values HIGH and LOW. In one tool, they introduce a variable alpha ranging over HIGH and LOW, and a Boolean beta-1-high. Finally, there is some evidence that the authors did not even test the products hands-on, especially NExpert and Personal Consultant. The figures in the review that show the representations are not actual screens or direct printouts from the systems. Moreover, the two figures that clearly are copies of actual screens come from the vendor literature and reviews in other magazines, rather than from their own extended examples with Beta. In addition, there is no hard performance or benchmark data. Of course, there were two pages of "ES Strategies" besides the mid-sized tool discussion. These were devoted to news items and a calendar of ES events. It was rather standard fare, readily available in InfoWorld, Datamation, etc. in the same timeframe. The news was grouped together in one place, but was by no means exhaustive in its coverage. In summary, based on this issue, I might spend $10-20 for a year's subsription, but certainly not for a single issue. Like many of the AI tools themselves, it seems overpriced by at least an order of magnitude. However, in case you're interested in finding out for yourself, "Expert Systems Stragtegies" is published by Cutter Information Corp. 1100 Massachusetts Avenue Arlington, MA 02174-9990 Phone: (617) 648-8700 Telex: 650 100 9891 MCI UW Dallas Webster CMP.BARC@R20.UTexas.Edu {ihnp4 | seismo | ctvax}!ut-sally!batman!dallas ------------------------------ Date: 27 May 86 18:06:54 GMT From: ihnp4!ihlpg!portegys@ucbvax.berkeley.edu (Tom Portegys) Subject: Insect rituals Observing the amazing behavior of a wasp constructing its nest, I was brought to wonder at the procedures which bring about this performance. It occurred to me that if complete algorithms were to be constructed for the complexity of the wasp's environment, such as lighting, nest location, and material, that the algorithms would also have to be incredibly complex. If, however, rituals were used - small pieces of invariant stimulus-response behavior which serve to signify the state of the world, then I would guess that a simple set of algorithms may be made to operate in a complex environment. I remember not too long ago hearing that someone had indeed found something like this to be true for a certain insect - that if it was disrupted in its nest building at some point, then it would go back to the beginning and start over. This also reminds me of Simon's Ant, which looks like it is employing a very complicated procedure to cross a pebble covered beach, but most of the complexity is in the environmet, not the ant. A ritual would be a highly structured stream of stimulus-response pairs. It must have an initiating stimulus(i). If in the course of performing the ritual, an incomplete condition is observed, for example, a circular nest area is not complete, then it would trigger another behavior to rectify the situation, for example, go get more nesting material. In addition to nest building behavior, homing abilities could be explained by specific pattern matching schemes. For example, in order to find its nest, a bee may rely on a specific pattern of ground figures (which may be transformed internally to account for the position of the sun). Upon not finding the specific pattern, it would commenced a seek behavior (perhaps a spiral search) until the pattern matches. The often elaborate courting and signaling rituals of insects also tends to support the requirement that a specific sequence of stimulus-response's is at work. I also think that in simpler life forms, the senses of smell and hearing are overlooked in importance by the vision dominated creatures that we are. With smell and hearing , a simple set of mechanisms can be utilized to provide effective seeking performance for food, home, mates, etc, since the organism simply moves in the direction of the stronger odor or sound. Tom Portegys, ..ihnp4!ihlpg!portegys AT&T Bell Labs ------------------------------ Date: 29 May 86 01:51:00 GMT From: cad!nike!ll-xn!mit-amt!bc@ucbvax.berkeley.edu (William H Coderre) Subject: References from my thesis A while back I sent a note asking for references in regard to animal behavior simulation using rule systems. Well, my thesis is done, and here's the references I got. (I know that some of them are not very complete. If I had more info, I woulda put it in...) If anyone desperately needs any of the below, or wants a copy of my thesis, feel free to drop me a note. I'll try to help out....bc ________ Agre, Phil, Routines, MIT AI Laboratory Memo 828, May 1985. Alkon, Daniel L., Learning in a Marine Snail, Scientific American, June 1983, pp 70 P 84. Amari, Tom, and Druin, Allison, The Role of Graphics in Expert Systems, MIT Visible Language Workshop Memo {available through author of paper}, May 1986. Batali, John, Computation Introspection, MIT AI Lab Memo number 701, February 1983. Braitenberg, Valentino, Vehicles: Experiments in Synthetic Psychology, MIT Press, 1984. Camhi, Jeffrey M., The Escape System of the Cockroach, Scientfic American, December 1982, pp 158 - 172. Davis, James R., Pesce, computer program modelling fish behavior, September, 1983. Davis, Randall, Meta-Rules: Reasoning about Control, MIT AI Lab Memo number 576, March 1980. Greilich, Horst, Vehicles, software package for Apple Macintosh, MIT Press, 1986. Hofstadter, Douglas R., The Copycat Project: An Experiment in Nondeterminism and Creative Analogies, MIT AI Lab Memo number 755, January 1984. Jacobs, Walter, How a Bug's Mind Works {paper in unidentified book; author has listed affiliation with American University, Washington DC}. Kay, Alan C., Trial Vivarium Curriculum, Trial User Interface, Trial Vivarium Graphics and Animation, Trial Vivarium Moist Models, 1985 {four papers on aspects of the Vivarium project, available by contacting author}. Kay, Alan C., Computer Software, chapter of Computer Software, Scientific American, 1984. Kehler, Thomas P., and Clemenson, Gregory D., KEE, The Knowledge Engineering Environment for Industry, Intelligenetics, Inc., 1983 {paper available from Intelligenetics, 124 University Ave, Palo Alto, CA}. Lenat, Douglas B., Beings: Knowledge as interacting experts, Procedings of the Fourth IJCAI, pp 126 - 133, 1975. Lenat, Douglas B., and Harris, Gregory, Designing a Rule System that Searches for Scientific Discoveries, CMU Department of Computer Science. Lenat, Douglas B., and Brown, John Seeley, Why AM and EURISKO Appear to Work, Artificial Intelligence, 1984, pp 269 P 294. Lorenz, Konrad, King Solomon's Ring, Thomas Y. Crowell Company, 1952. MacLaren, Lee S., A production system architecture based on biological examples, PhD thesis, U. Washtington Seattle, 1978 {available as University Microfilms order number 79-17604}. Minsky, Marvin, The Society of Mind, Simon and Schuster, 1986 or 1987 {this author greatly thanks Professor Minsky for a pre-publication copy of his forthcoming book}. Robot Odyssey I, The Learning Company {computer game widely available}. Stefik, Mark, et al., Knowledge Programming in Loops: Report on an Experimental Course, AI Magazine, Fall 1983. Various Authors, The Brain, Scientific American, 1979. ------------------------------ Date: 29 May 86 07:04:18 GMT From: cad!nike!think!bruce@ucbvax.berkeley.edu (Bruce J. Nemnich) Subject: Re: Help on Thinking Mach. Inc. Hi. Yes, Thinking Machines is indeed on the net, though we don't have many people here who read news. Let me try to address your questions. I'm adding net.ai to the distribution since they are probably interested in the Connection Machine System, too. > * How is the CM programmed? > ... > The Connection Machine Lisp manual is, evidently, unavailable to those > of us who do not have a million dollars to by a CM. The CMLisp manual isn't available becuase the language is still in the design and implementation phases; i.e., it's not stable enough yet to give out manuals. It certainly has nothing to do with money. It will be a lot like the language in Danny Hillis's book (which was written before we had working hardware). I hear there will be a paper on it by Danny and Guy Steele at an upcoming Lisp conference; sorry I don't know the details. Many people have many different ideas about how to program the CM, and there has already been quite an evolution of lisp-based languages here in the last couple of years. The language we are distributing with the first machines is *Lisp ("star-lisp"), which consists of a large collection of functions and macros for defining and manipulating parallel datatypes which live in the CM from lisp. There is also a language being implemented called C* ("C-star"), which is an extention to C which handles CM datatypes and control flow. The extensions, which have the syntatic flavor of C++, provide sophisticated ways of defining layouts of data on the CM, provide control flow, etc. There's no one answer to "How does one program the CM?", but most applications to which the CM (or any fine-grained SIMD architecture) is particularly well-suited have some kind of inherent data-level parallelism; i.e., similar computations on a large number of data points. Typically each datum is assigned a processing element. Given that, there are two common classes of problems: graph problems and grid problems. For example, the CM's "connections" give the ability for one datum to point to other(s), so arbitrary data graphs can be constructed. Such a graph could be searched for a given datum in constant time: every processor just compares its value to the desired value (regular SIMD, no use of pointers). Distance on the graph between two data can be found in time proportional to the distance by chasing pointers (fanning out) in parallel from one until one of the paths reaches the other. Simple logic simulation can be done by setting up such a graph with the outputs of one element pointing to an input of another. Each element would compute output values based on its inputs and pass them along to the next level. The grid problems are those which also rely on communication between elements but don't require general pointers; they only require local communication on a cube or grid. The Connection Machine has facilities for local communication on the cube or grid which are faster than the more general pointer-like mechanism. > Imagine a message is traveling through the CM and it encounters a hot > spot. The message is rerouted. Just after it is rerouted, the > congestion clears and the next message to that destination goes > through the direct binary n-cube path. The two messages may now be > out of order, since the second message could arrive before the first. Messages are addressed to a given processor and memory address within the processor. Usually an operation is something like "everyone who is currently selected send the N bits in your memory beginning at S to the processor whose address is stored in your memory at M, and put them in his memory at D." If there are collisions in destinations (two or more are both trying to send to the same processor/address), they are combined in some way (current choices are: IOR, AND, XOR, ADD, MIN, MAX, OVERWRITE (overwrite means just one is delivered)). There is no order to messages within a delivery cycle. One could sum a field over all the processors by having everyone send the field to processor 0 and specifying to combine collisions by adding them together (there are more efficient ways of doing this, though). > * How does the CM handle processor failure? > How are messages rerouted to avoid the failed PE? You're right, fault tolerance is very important. We have though about it, though there's a lot we want to implement which isn't yet in the hardware. The current hardware/software basically assumes things are working. Reasonably quick diagnostics can be run to verify with high confidence that nothing's broken. Almost all failures are on CM matrix boards, of which there are 128 identical copies in a 64k-proc CM. They're easy to swap. But since we think a 64k CM is small, serious fault-tolerance is necessary. The "router" is the general message-routing mechanism, one for every 16 processors, currently arranged in a hypercube. There is currently hardware support for turning off paths (a cube edge) between routers. If a wire between two routers was broken, that path could be turned off in software. If a whole router was broken (or perhaps the processors which belong to it), all paths to it could be turned off. If a message would normally go over that path, it would instead go another direction (preferably, but not necessarily, another direction the message wanted to go). However, fault tolerance on the local grid and cube communication is more of a problem, since applications using them typically rely on the regular topology. A glitch in a 2-d grid, for instance, could be ignored by effectively bridging out that row and column of the grid. We don't have any support for that, though. > Thinking Machines has been, at least with me, very secretive about the > CM. > Once a machine is released for sale, information must be released to > sell it. Absolutely. On behalf of whomever you talked to, sorry. We don't mean to be secretive. We have just been through the period of getting ready trying to announce the machine, scrambling to gather/write the kind of information you want, and trying to put in place mechanisms to distribute it. We WANT people to know and think lots about Connection Machines. Hope I've been of help. Just in case I'm supposed to say this, "Connection Machine" is a registered trademark of Thinking Machines Corporation. :-) -- --Bruce Nemnich, Thinking Machines Corporation, Cambridge, MA --bruce@think.com, ihnp4!think!bruce; +1 617 876 1111 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 19:00:13 1986 Date: Thu, 5 Jun 86 18:59:59 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #138 Status: R AIList Digest Wednesday, 4 Jun 1986 Volume 4 : Issue 138 Today's Topics: Queries - Lisp for Silicon Graphics Machines & Conditional Independence in Possibility & Curve Fitting Software, Techniques - Lazy Evaluation, Psychology - Inside Out, Description - UMich Cognitive Science and Machine Intelligence Lab ---------------------------------------------------------------------- Date: Tue, 03 Jun 86 10:36:40 -0400 From: ritter@dewey.udel.EDU Subject: Lisp for Silicon Graphics machines Our research group (in Chemical Engineering) at the University of Delaware has just purchased a Silicon Graphics 3030 workstation, a new version of the 2400 turbo. We are intersested in obtaining a version of LISP to use with the machine. Does anyone know what version/company is the best to use? We plan to build an expert system to predict phase behavior and are using the Silicon Graphics to display the desired graphics output. So far, the only company we know of if FranzInc. in CA. which sells a version of franzlisp. (We are a little inclined towards a version of Common, since it is somewhat more universal.) Any comments or suggestions would be welcomed. Thank you, Joe Ritter ritter@dewey.udel.edu ------------------------------ Date: 3 Jun 86 02:59:23 GMT From: sdcsvax!caip!seismo!kaist!cskaist!dhkim2@ucbvax.berkeley.edu (Doohyun Kim) Subject: Conditional independence in possibility Hi! I'm DOOHYUN KIM at KAIST(Korea Advanced Institute of Science and Technology). It is first time for me to broadcast on these news group. I'm now search some papers about "Conditional independence of possibility" These papers are very important in my Master Thesis. Is there anyone who has following papers ? Do you have any ideas about how to get these papers? [1] E. Hisdal, "Conditional possibilities - Independence and non-interactivity," Fuzzy Sets Systems., vol. 1, pp 283-297, 1978. [2] E. Hisdal, "A fuzzy 'if then else' relation with guaranteed correct inference," in Applied System and Cybernetics, G.E. Lasker, Ed. New York: Pegamon, pp. 2906-2911; also in Fuzzy set and possibility theory: recent developments, R. R. Yager, Ed. New York: Pegamon, 1982, pp 204-210. [3] H. T. Nguyen, "On conditional possibility distributions," Fuzzy Sets Systems, Vol 1, pp 299-309, 1978. Please send a copy to me, if you have. electlic mail path : dhkim2%cskaist%kaist.csnet@CSNET-REPLY mail address : DOOHYUN KIM Dept. of Computer Science, P.O. BOX 150, CHEONGRYANG, SEOUL, KOREA 150 ------------------------------ Date: Mon 2 Jun 86 12:07:28-PDT From: Charlie Koo Subject: Query: curve fitting I'm interested in getting some information about available software (for IBM PC) for doing curve fitting. More specifically, given the digitized image of a circle or part of a circle (2-D), how could we decide: . whether it is a circle . what the center and radius of the circle should be? Thanks. Charlie ------------------------------ Date: Tue, 3 Jun 86 10:41 EDT From: Stephen G. Rowley Subject: Lisp & Lazy Evaluation in AIList Digest V4 #135 Date: Mon, 2 Jun 86 09:27 N From: DESMEDT%HNYKUN52.BITNET@WISCVM.WISC.EDU In AIList Digest V4 #134, Mike Maxwell reluctantly prefers the efficiency of a hand-coded "do" construction in Lisp, although mapping a function on a list would be more elegant. Indeed, mapping sometimes causes many unnecessary computations. Consider the following example: (defun member (element list) (apply 'or (mapcar #'(lambda (list-element) (eql element list-element)) list))) I can't help but point out that, if you're using Common Lisp, this function is strange on several accounts: [1] It shadows MEMBER, which can't be a good idea. [2] It tries to return the first thing in the list eql to element, whereas the real MEMBER returns a tail of the list or NIL. [3] It attempts to apply OR, which is a special form and hence cannot be applied. In this case, you'd use SOME instead. Obviously, though, I'm just quibbling with your example. Let's move on: Your statements about the general wastefulness of mapping functions are true, if you restrict yourself to MAPCAR and friends. However, if you write your own mapping functions, they can be quite elegant. Here's an example. I was writing a discrimination net for a pattern database. Given a pattern, it would search a database for things that might unify with it, and do something to all of them. (See, for example, Charniak, Riesbeck, & McDermott's "Artificial Intelligence Programming", chapters 11 & 14.) For example, a program might want to print everything that unified with the pattern (foo a ?x), where ?x is a variable. The first implementation cried out for lazy evaluation; I didn't want to compute a list of all the patterns because of consing effects. The top-level search function returned a stream object (simulation of laziness) which could be prodded to produce the next answer: (loop with stream = (search-for-pattern '(foo a ?x)) for next = (next-element stream) while next doing (print next)) The second implementation got smarter and made the callers of the search function package up their intentions in a closure. The search function would then apply that closure to patterns that it found. The result is something very mapping-like: (search-for-pattern '(foo a ?x) #'print) The second implementation also turned out to be faster and consed less, although it did use up some more stack space than the first. Moral: Appropriate use of function closures can often (although not always) satisfy your needs for lazy evaluation. ------------------------------ Date: Sat, 31 May 86 15:38:33 bst From: gcj%qmc-ori.uucp@Cs.Ucl.AC.UK Subject: Inside Out. This posting is a tangential response to Pat Hayes' posting in AIList Vol 4 # 125. It is obvious to every child that two things cannot exist in the same place at once. But a child does not know what is the other side of the cradle. A child (and therefore the adult) can never fully expand its spatial reasoning beyond what the eye can see. Hence, we enter a new realm; fantasy. For example:- It is even possible to believe that if I walk into this room, I will leave reality and enter into a fantasy, eg a film, OR I wake up one morning and am afraid to open the door in case I do not recognise the landscape outside. We carry childhood stories and myths with us to the grave; we remember the lessons we learnt not only in books and from our schooling, but also the fairy stories, eg "Alice Through the Looking Glass" and "The Lion, the Witch and the Wardrobe". This is more about the distinction between fantasy and reality than to do with spatial intuition. In the Mind's I, there is a discussion on whether or not a simulation inside a computer of a hurricane is any different from the machine's perception of the real event. To me there would be a world of difference! In "The Teachings of Don Juan: A Yaqui Way of Knowledge" by Carlos Castaneda, the author describes, at some point in the book, his transformation into a bird. His forward begins with the sentence - "This book is both ethnography and allegory." But my reading is that he wants you to *believe* his story. "Choose your own paradigm of reality." -- The Joka. Gordon Joly ARPA: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Sat, 31 May 86 15:59:20 bst From: gcj%qmc-ori.uucp@Cs.Ucl.AC.UK Subject: Inside Out - Postscript. The best model we have for the universe is Einstein's theory of general relativity, which models the cosmos as a 4 dimen- sional pseudo-Riemannian spacetime. The geometry of such a model is far from intuitive. Gordon Joly ARPA: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Mon 2 Jun 86 10:24:35-PDT From: Ken Laws Subject: Inside Out Some thoughts on Pat Hayes' question: My own intuition is that either 1) the Tardis is simply bigger inside, as you suggest, or 2) the doorway is a portal to another dimension or reality that could contain anything at all. One way to test the intuition is to ask "What would happen if I cut a hole through the wall?" The answer would not completely distinguish the two cases, since it is quite possible that the entire wall (inside and out) is a portal that maps between two realities; cutting a hole would create a new door with exactly the same properties as the original, which would tell us nothing. My own guess, though, is that cutting a hole from outside the Tardis would reveal some kind of "machinery" or peculiar spatial structure (such as a gel, crystal, or other "matrix"), while cutting a hole from the inside would let you out into Gallifrey, Dr. Who's natural environment. Such portals have been frequent in science fiction, and the exact properties that we infer for each depends on the author's presentation. Some conceptions do lead to greater difficulties than others. In Robots Have No Tails, Louis Padgett (pseudonym) wrote about a box that was larger inside [partly] because it mapped into the future and the universe was shrinking. This lead to difficulties at the interface: things put inside would shrink, but only after a few seconds, and it is not clear what would happen to a single object such as your hand that extended across the portal for that length of time. I find Pat's "shrinking" hypothesis untenable for this reason. Similar problems arise at the boundary if the doorway is a transporter. Another such box is the chest that appears in one episode of the Dungeons and Dragons cartoon on TV. Move it to a particular place, open it, and you are likely to find a stairway to an alternate reality. (This is rather like the holes in time used in the Time Bandits movie.) The D&D chest has the property that the spatial mapping between realities is fixed and that the portal itself moves between them. I assume that the box cannot be moved while open, which helps cover the main conceptual difficulty: why realities only connect at certain points, and what happens if the box straddles two such points. As for something simply being bigger inside, this doesn't bother me. As we move, we somehow update our internal maps of our surroundings. As I turn my head, I somehow rotate my mapping of where everything is relative to my focal direction. It seems unlikely that I actually store and update a position vector for every book on my bookshelves; instead I must be storing relative positions of items in the room and the relative orientation of myself and the room. One could argue that our natural tendency to build walls, and perhaps even our tendency to build rectangular rooms, arises from the mental savings in building these maps in hierarchically partitioned modules with related coordinate frames. If we store spatial relations in such a manner, it is easy to see how the spatial relationships inside a box need not be strongly linked to those outside the box. Just as we can move the box and its contents as a whole, we can expand it as a whole (on the inside only!) without affecting our mapping of the rest of the world. As for two things not occupying the same space, that's not really true. It all depends on what you mean by "thing". A forest and a tree occupy overlapping space. Properties such as color and texture certainly coexist. Fish and streams seem to interoccupy, and groping around in streams and holes may be a task for which our spatial decoupling evolved. I wouldn't even be surprised if fish were perceptually bigger on the inside than on the outside, since they disgorge a lot of "stuff" when you open them up that is perceived at a different level of detail than is the smooth exterior of a fish. -- Ken Laws ------------------------------ Date: Sun, 1 Jun 86 20:06:44 EDT From: Gary_M._Olson%UMich-MTS.Mailnet@MIT-MULTICS.ARPA Subject: Description - UMich Cognitive Science and Machine Intelligence Lab THE COGNITIVE SCIENCE AND MACHINE INTELLIGENCE LABORATORY The University of Michigan Ann Arbor, Michigan The Cognitive Science and Machine Intelligence Laboratory (CSMIL) is an interdisciplinary organization, spanning the fields of artificial intelligence, cognitive science, and human-computer interaction. It is sponsored by three colleges at the University of Michigan: the Graduate School of Business Administration, the College of Engineering, and the College of Literature, Science, and the Arts (LSA). Its mission is to facilitate faculty research and graduate training, with a special focus on cross-college collaborations. CSMIL faculty are interested in a variety of specific topics in cognition, such as vision, attention, learning, reasoning, and problem-solving, whether they are in humans or machines. Some are also interested in designing and evaluating the interface between humans and computer systems, or in developing computer tools to augment and extend human cognition. CSMIL faculty have a broad range of experience in methods relevant to these problems, including such areas as the design of special computer architectures, software design and evaluation, artificial intelligence programming, and the analysis of human cognition. CSMIL has a range of specific activities. It sponsors various seminars, colloquia, conferences, and workshops on the U of M campus in order to facilitate interdisciplinary intellectual exchange. Many of these are open to the general technical community in the area as well as to U of M faculty and students. Periodically, CSMIL will sponsor a single set of focused intellectual activities designed to stimulate progress in one particular research frontier, devoting an entire semester or academic year to intellectual exploration of an important topic. CSMIL coordinates financial support for faculty projects, and also assists in developing shared research facilities. CSMIL also takes an active role in disseminating results from the research of U of M faculty through several publication series tailored to either specific technical audiences or a more general readership. Finally, CSMIL has a Corporate Affiliates Program through which U of M faculty and their peers in corporations can interact on a regular basis. For further information about any of these activities, contact: Gary M. Olson, Director Cognitive Science and Machine Intelligence Laboratory The University of Michigan 904 Monroe Street Ann Arbor, Michigan 48109 313-747-4948 Net address: Gary_Olson%UMich-MTS.Mailnet@MIT-Multics.Arpa ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 18:59:58 1986 Date: Thu, 5 Jun 86 18:59:46 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #139 Status: R AIList Digest Wednesday, 4 Jun 1986 Volume 4 : Issue 139 Today's Topics: Literature - New Category Codes & Technical Reports #1 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: new category codes AI15 Truth Maintenance and Non-Monotonic logic AI16 General AI, Unclassifiable AI, Theory of AI, Philosphy of AI (things that need one of these classifications but don't fit in any particular one) AA26 manufacturing AA27 space O06 useful Algorithms, e. g. string matching, computational geometry ------------------------------ Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: some definitions D BOOK28 IEEE International Conference on Robotics and Automation\ %D April 7-10 1986\ %C San Francisco, CA D MAG19 Soviet Engineering Research\ %V 5\ %N 4\ %D APR 1985 D MAG20 Data Processing\ %V 28\ %N 1\ %D JAN - FEB 1986 D MAG21 Information Systems\ %V 11\ %N 1\ %D 1986 D BOOK29 STACS 86, Third Annual Symposium on Theoretical Computer Science\ %E B. Monien\ %E G. Vidal-Naquet\ %S Lecture Notes in Computer Science\ %V 210\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1986\ %X $20.50 soft bound ISBN 3-540-16078-7 D MAG22 IBM Journal of Research and Development\ %V 30\ %N 1\ %D JAN 1986 D MAG23 Computer Design\ %V 25\ %N 4\ %D FEB 15 1986 D BOOK30 Rewriting Techniques and Applications\ %E J. P. Jouannaud\ %S Lecture Notes inComputer Science\ %V 202\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1986\ %X 440 pages 23 chapters $22.80 ISBN 3-540-15976-2 D MAG24 Optical Engineering\ %V 25\ %N 3\ %D MAR 1986 D BOOK31 Mathematical Methods for Investigating the\ Natural Resources of the Earth from Space\ %I Nauka\ %C Moscow\ %D 1984 D BOOK32 Mathematization of Scientific: Knowledge: Paths\ and Trends\ %I Kazan Gos. Univ\ %C Kazan\ %D 1984 D BOOK33 International Symposium on Programming\ %S Lecture Notes in Computer Science\ %V 202\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1986 D BOOK34 Industrial Applications of Fuzzy Control\ %E M. Sugeno\ %I North Holland\ %D 1985 D BOOK35 Logics of Programs\ %S Lecture Notes in Computer Science\ %V 193\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D MAG24 Mechanism and Machine Theory\ %V 20\ %N 6\ %D 1985 D MAG25 Pattern Recognition\ %V 18\ %N 6\ %D 1985 D MAG26 Information and Control\ %V 63\ %N 1-2\ %D OCT-NOV 1984 D MAG27 The Journal of the Operations Research Society\ %V 37\ %N 1\ %D JAN 1986 D MAG28 John Hopkins Apl Technical Digest\ %V 7\ %N 1\ %D JAN-MAR 1986 D MAG29 Journal of Robotic Systems\ %V 3\ %N 1\ %D SPRING 1986 D BOOK36 Logics and Models of Concurrent Systems (La Colle-sur-Loup 1984)\ %S NATO Adv. Sci. Inst. Ser. F: Comput. Systems Sci\ %V 13\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D BOOK37 Combinatorial Algorithms on Words (Maratea, 1984)\ %S NATO Adv. Sci. Inst. Ser. F: Comput. Systems Sci.\ %V 12\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D BOOK38 Theoretical Aspects of Reasoning About Knowledge\ %E Joseph Y. Halpert\ %I Morgan Kaufman Publishers, Inc.\ %C Palo Alto, CA\ %D 1986\ %X ISBN 0-934613-0404 $18.95 D BOOK39 Eurocal 85, Volume 1\ %S Lecture Notes in Computer Science\ %V 203\ %E B. Buchberger\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D BOOK40 Foundations of Software Technology and Theoretical Computer Science\ %S Lecture Notes in Computer Science\ %V 206\ %E S. N. Maheshwari\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D MAG30 Werkstattstechnik WT Zeitschrift fur Industrielle Fertigung\ %V 76\ %N 1\ %D JAN 1986 D MAG31 International Journal of Robotics Research\ %V 4\ %N 4\ %D Winter 1986 D BOOK41 Artificial Intelligence: Toward Practical Application\ %S GDI Technology Assessment and Management\ %V 1\ %E T. Bernold\ %E G. Albers\ %I North Holland Publishers Co\ %C Amsterdam\ %D 1985 D MAG32 Manufacturing Engineering\ %V 96\ %N 4\ %D APR 1986 D MAG33 Intech\ %V 33\ %N 4\ %D 1986 D MAG34 Roboterstysteme\ %V 2\ %N 1\ %D 1986 D MAG35 Robotica\ %V 3\ %N Part 4\ %D OCT-DEC l985 D MAG36 Journal of Dynamics Systems, Measurement and Control\ %V 107\ %N 4\ %D DEC 1985 D MAG37 Robotersysteme\ %V 1\ %N 4\ %D 1985 D MAG38 International Journal of Man-Machine Studies\ %V 23\ %N 3\ %D SEP 1985 ------------------------------ Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Technical Reports #1 %A John W. Lloyd %A Rodney W. Topor %T Making Prolog More Expressive %R Technical Report 84/8 %I Department of Computer Science, University of Melbourne %D June 1984 %P 22 %K first order logic, programming in logic, deductive databases, query language AI10 AA14 AA09 %O also in Journal of Logic Programming, vol.4, 1984 %X This paper introduces extended programs and extended goals for logic programming. A clause in an extended program can have an arbitrary first order formula as its body. Similarly, an extended goal can have an arbitrary first order formula as its body. The main results of the paper are the soundness of the negation as failure rule and SLDNF-resolution for extended programs and goals. We show how the increased expressibility of extended programs and goals can be easily implemented in any PROLOG system which has a sound implementation of the negation as failure rule. We also show how these ideas can be used to implement first order logic as a query language in a deductive database system. An application to integrity constraints in deductive database systems is also given. %A Jacek Gibert %T J-Machine User's Manual %R Technical Report 84/10 %I Department of Computer Science, University of Melbourne %D November 1984 %P 42 %K functional programming, graph reduction machines, combinators H03 %X This manual describes an experimental software implementation of a combinatory reduction machine called the J-Machine. The J-Machine is mainly oriented towards symbol manipulation and it aims at exposing flows of data, and a high degree of parallelism in ordinary functional programs. It executes directly the J'' reduction language which is based upon a variant of the full combinatory theory. The J'' language has an associated algebra of functions which allows a user to prove properties of functional programs with the assistance of the J-Machine. With the advent of hardware concepts like data driven reduction architectures, VLSI implementation of the J-Machine appears to be an attractive proposition. But at the present, the J-Machine is an interactive interpreter written in the C programming language under the Unix operating system. %A Lee Naish %T Prolog Control Rules %R Technical Report 84/13 %I Department of Computer Science, University of Melbourne %D September 1984 %P 12 %K AI10 computational rules %O a shortened version appeared in Proceedings of the International Joint Conference on Artificial Intelligence, Los Angeles, 1985 %A Joxan Jaffar %A Jean-Louis Lassez %A Michael J. Maher %T A Logic Programming Language Scheme %R Technical Report 84/15 %I Department of Computer Science, University of Melbourne %D November 1984 %P 22 %K theory, semantics AI10 T02 %O also appeared in Logic Programming: Relations, Functions and Equations'', D.DeGroot and G.Lindstrom (eds.), Prentice-Hall, 1985 %X Numerous extended versions of PROLOG are now emerging. Im order to provide greater versatility and expressive power, some versions allow functional programming features, others allow infinite data structures. However, there is concern that such languages may have little connection left with logic. In some instances, various logical frameworks have been proposed to solve this problem. Nevertheless, the crucial point has not been addressed: the preservation of the unique semantic properties of logic programs. The significance of our effort here is twofold: (1) There is a natural logic programming language scheme wherein these properties hold. (2) Formal foundations for extended versions of traditional PROLOG can be obtained as instances of this scheme. They automatically enjoy its properties. %A T. Y. Chen %A Jean-Louis Lassez %A Graeme S. Port %T Maximal Unifiable Subsets and Minimal Non-unifiable Subsets %R Technical Report 84/16 %I Department of Computer Science, University of Melbourne %D November 1984 %P 20 %K unification, backtracking, resolution AI11 %A John W. Lloyd %A Rodney W. Topor %T A Basis for Deductive Database Systems %R Technical Report 85/1 %I Department of Computer Science, University of Melbourne %D February 1985 (revised April 1985) %P 22 %K logic programming, first order logic, soundness, integrity constraints AA14 AA09 T02 %X This paper provides a theoretical basis for deductive database systems. A deductive database consists of closed typed first order logic formulas of the form A<-W, where A is an atom and W is a typed first order formula. A typed first order formula can be used as a query and a closed typed first order formula can be used as an integrity constraint. Functions are allowed to appear in formulas. Such a deductive database system can be implemented using a PROLOG system. The main results are the soundness of the query evaluation process, the soundness of the implementation of integrity constraints, and a simplification theorem for implementing integrity constraints. A short list of open problems is also presented. %A Richard A. Helm %A Catherine Lassez %A Kimball G. Marriott %T Prolog for Expert Systems: An Evaluation %R Technical Report 85/3 %I Department of Computer Science, University of Melbourne %D June 1985 %P 20 %K TEAS, MARLOWE, knowledge representation AI01 T02 %O also in Proceedings of Expert Systems in Government'', Virginia, 1985 %A John W. Lloyd %A Rodney W. Topor %T A Basis for Deductive Database Systems II %R Technical Report 85/6 %I Department of Computer Science, University of Melbourne %D February 1985 (revised April 1985) %P 17 %K AI10 first order logic, soundness, integrity constraints, query evaluation AA09 AA14 %X This paper is the third in a series providing a theoretical basis for deductive database systems. A deductive database consists of closed typed first order logic formulas of the form A<-W, where A is an atom and W is a typed first order formula. A typed first order formula can be used as a query and a closed typed first order formula can be used as an integrity constraint. Functions are allowed to appear in formulas. Such a deductive database system can be implemented using a PROLOG system. The main results of this paper are concerned with the non-floundering and completeness of query evaluation. We also introduce an alternative query evaluation process and show that corresponding versions of the earlier results can be obtained. Finally, we summarize the results of the three papers and discuss the attractive properties of the deductive database system approach based on first order logic. %A Lee Naish %T The MU-Prolog 3.2 Reference Manual %R Technical Report 85/11 %I Department of Computer Science, University of Melbourne %D October 1985 %P 17 %K AI10 T02 %X MU-PROLOG is (almost) upward compatible with DEC-10 PROLOG, C-PROLOG and (PDP-11) UNIX PROLOG. The syntax and built-in predicates are therefore very similar. A small number of DEC-10 predicates are not available and some have slightly different effects. There are also some MU-PROLOG predicates which are not defined in DEC-10 PROLOG. However most DEC-10 programs should run with few, if any, alterations. However, MU-PROLOG is not intended to be a UNIX PROLOG look-alike. MU-PROLOG programs should be written in a more declarative style. The non-logical predicates'' such as cut (!), \\=, not and var are rarely needed and should be avoided. Instead, the soundly implemented not (~), not equals (~=) and if-then-else should be used and wait declarations should be added where they can increase efficiency. This is a reference manual only, not a guide to writing PROLOG programs. %A Lee Naish %T Negation and Control in PROLOG %R Technical Report 85/12 %I Department of Computer Science, University of Melbourne %D September 1985 %P 108 %K T02 resolution, PhD thesis %X We investigate ways of bringing PROLOG closer to the ideals of logic programming, by improving its facilities for negation and control. The forms of negation available in conventional PROLOG systems are implemented unsoundly, and can lead to incorrect solutions. We discuss several ways in which negation as failure can be implemented soundly. The main forms of negation considered are not'', not-equals'', if-then-else'' and all solutions predicates. The specification and implementation of all solutions predicates is examined in detail. Allowing quantifiers in negated calls is an extension which is easily implemented and we stress its desirability, for all forms of negation. We propose other enhancements to current implementations, to prevent the computation aborting or looping infinitely, and also outline a new technique for implementing negation by program transformation. Finally, we suggest what forms of negation should be implemented in future PROLOG systems. %A Lee Naish %T Negation and Quantifiers in NU-Prolog %R Technical Report 85/13 %I Department of Computer Science, University of Melbourne %D October 1985 %P 12 %K T02 control %X We briefly discuss the shortcomings of negation in conventional Prolog systems. The design and implementation of the negation constructs in NU-Prolog are then presented. The major difference is the presence of explicit quantifiers. However, several other innovations are used to extract the maximum flexibility from current implementation techniques. These result in improved treatment of \*(lqif\*(rq, existential quantifiers, inequality and non-logical primitives. We also discuss how the negation primitives of NU-Prolog can be added to conventional systems, and how they can improve the implementation of higher level constructs. %A Michael J. Maher %T Semantics of Logic Programs %R Technical Report 85/14 %I Department of Computer Science, University of Melbourne %D September 1985 %P 77 %K logic programming theory, fixed points, fixedpoints, PhD thesis AI10 %X This thesis deals with the semantics of definite clause logic programs in the presence of an equality theory. Definite clauses are the formal foundation of the PROLOG programming language. Definitions of functions and abstract data types use equality. Many have suggested the incorporation of these features into a logic programming language and already there are many of these languages. This thesis provides a formal foundation for such languages. The treatment consistently factors out the equality theory to obtain the effect of a scheme: any equality theory which satisfies some appropriate conditions can be used as part of the programming language. %A Philip W. Dart %A Justin A. Zobel %T Conceptual Schemas Applied to Deductive Databases %R Technical Report 85/16 %I Department of Computer Science, University of Melbourne %D November 1985 %P 29 %K prolog, query language, graphical interface, conceptual schema, deductive database AI10 %X Much of the information required in the formulation of a query is inherent in the database structure. First order logic is a powerful query language, but does not exploit this structure or provide an accessible interface for naive users. A new conceptual schema formalism, based directly on logic, provides the necessary description of the database structure. Its graphical representation is the basis for a simple, concise graphical query language with the expressive power of first order logic. %A Kotagiri Ramamohanarao %A John A. Shepherd %T A Superimposed Codeword Indexing Scheme for Very Large Prolog Databases %R Technical Report 85/17 %I Department of Computer Science, University of Melbourne %D November 1985 %P 20 %K partial match retrieval, Prolog, hashing, descriptors, optimization T02 AA09 %X This paper describes a database indexing scheme, based on the method of superimposed codewords, which is suitable for dealing with very large databases of Prolog clauses. Superimposed codeword schemes provide a very efficient method of retrieving records from large databases in only a small number of disk accesses. This system supports the storage and retrieval of general Prolog terms, including functors and variables, and it is possible to store Prolog rules in the database. %A James A. Thom %A Kotagiri Ramamohanarao %A Lee Naish %T A Superjoin Algorithm for Deductive Databases %R Technical Report 86/1 %I Department of Computer Science, University of Melbourne %D February 1986 %P 10 %K partial match retrieval, prolog, hashing, joins, optimization, database relational, deductive AI10 AA09 %X This paper describes a join algorithm suitable for deductive and also relational databases which are accessed by computers with large main memories. Using multi-key hashing and appropriate buffering, joins can be performed on very large relations more efficiently than with existing methods. Furthermore, this algorithm fits naturally into a Prolog top-down computation and can be made very flexible by incorporating additional Prolog features. %A Lee Naish %T Don't Care Nondeterminism in Logic Programming %R Technical Report 86/? %I Department of Computer Science, University of Melbourne %D February 1986 %P 10 %K indeterminism, incompleteness, cut, commit, trust, parallel, proving AI10 %X Prolog and its variants are based on SLD resolution, which uses don't know nondeterminism to explore the search space. Don't care nondeterminism, or indeterminism, can be introduced by operations such as commit in Concurrent Prolog, cut in sequential Prolog and incomplete system predicates. This prevents the whole SLD tree from being examined. The effect on completeness of programs is of major importance. This paper presents a theoretical model of \fIGuarded Clauses\fP, which subsumes the main features of sequential and concurrent Prologs. Next, we investigate proving properties of Guarded Clause programs with restricted input-output modes. We present a methodology for proving that the indeterminism does not cause finite failure, given certain input conditions. %A John W. Lloyd %T Declarative Error Diagnosis %R Technical Report 86/? %I Department of Computer Science, University of Melbourne %D February 1986 %P 20 %K algorithmic debugging, logic programming AI10 T02 O02 AI01 %X This paper presents an error diagnoser which finds errors in extended logic programs and also logic programs which use advanced control facilities. The diagnoser is declarative'', in the sense that the programmer need only know the intended interpretation of an incorrect program to use the diagnoser. In particular, the programmer needs no understanding whatever of the underlying computational behaviour of the PROLOG system which runs the program. It is argued that declarative error diagnosers will be indispensable components of advanced logic programming systems, which are currently under development. %A J. Heering %T Partial Evaluation and W-Completeness of Algebraic Specifications %D 1985 %R Report CS-R8501 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AA08 %X f 3,90 14 pages %A J. C. M. Baeten %A J. A. Bergstra %A J. W. Klop %T Conditional axioms and $alpha beta$ calculus in process algebra %D 1985 %R Report CS-R8502 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AA08 %X f 3,90 26 pages %A J. C. M. Baeten %A J. A. Bergstra %A J. W. Klop %T Syntax and Defining Equations for an Interupt Mechanism in Process Algebra %D 1985 %R Report CS-R8503 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AA08 %X f 7,60 45 p %A J. W. de\0Bakker %T Transition Systems, Infinitary Languages and the Semantics of Uniform Concurrency %D 1985 %R Report CS-R8506 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AA08 %X f 3,90 11 pages %A J. Heering %A P. Klint %T The Efficiency of the Equation Interpreter Compared with the UNH PROLOG Interpreter %D 1985 %R Report CS-R8509 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K T02 AI10 %X f 3,90 13 pages %A M. L. Kersten %A H. Weigand %A F. Dignum %T A Conceptual Modeling Expert System %D 1985 %R Report CS-R8518 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AI01 %X f 3,90 14 pages %A N. W. P. van\ Diepen %A W. P. de\ Roever %T Program Derivation Through Transformations: the Evolution of List-Copying Algorithms %D 1985 %R Report CS-R8520 %I Centre for Mathematics and Computer Science %C Amsterdam, The Netherlands %K AA08 %X f 8,80 60 pages %A Bertrand Meyer %T The Software Knowledge Base %R TRCS85-04 %I University of California, Santa Barbara %K AA08 %A Bernard Nadel %T The General Consistent Labeling (or Constraint Satisfaction) Problem %R CRL-TR-2-86 %I University of Michigan Computing Research Laboratory %K AI03 %A William G. Golson %T A Complete Proof System for an Acceptance Refusal Model of CSP %R TR85-19 %I Rice University Department of Computer Science %K AA08 %A Raghu Ramakrishman %A Avi Silberschatz %T Annotations for Distributed Programming in Logic %R TR-85-15 %D SEP 1985 %I University of Texas at Austin Department of Computer Sciences %K H03 T02 AI10 %A E. Allen Emerson %A Chin-Laung Lei %T Branching Time Logic Strikes Back %R TR-85-21 %D OCT 1985 %I University of Texas at Austin Department of Computer Sciences %K temporal logic finite automata infinite strings AA08 AI11 %A Christian Lengauer %A Chua-Huang Huang %T A Mechanically Certified theorem about Optimal Concurrency of Sorting Networks %R TR-85-23 %D OCT 1985 %I University of Texas at Austin Department of Computer Sciences %K H03 AI11 AA08 %A A. Udaya Shankar %A Simon S. Lam %T Time-Dependent Distributed Systems: Proving Safety, Liveness and Real-Time Properties %R TR-85-24 %D OCT 1985 %I University of Texas at Austin Department of Computer Sciences %K H03 AI11 A08 %X includes information on verification of communication protocols including HDLC and a transport-layer protocol of window size N %A E. Allen Emerson %A A. Prasad Sistla %T Deciding Full Branching Time Logic %R TR-85-28 %D NOV 1985 %I University of Texas at Austin Department of Computer Sciences %K AI10a %A E. Allan Emerson %A Joseph Y. Halpern %T Decision Procedures and Expressiveness in the Temporal Logic of Branching Time %R TR-85-29 %D NOV 1985 %I University of Texas at Austin Department of Computer Sciences %K AI10a %A E. M. Clarke %A E. A. Emerson %A A. P. Sistla %T Automatic Verification of Finite State Concurrent Systems Using Temporal Logic Specifications %R TR-85-31 %D NOV 1985 %I University of Texas at Austin Department of Computer Sciences %K AI10a H03 AA08 %A Benjamin Kuipers %T The Map-Learning Critter %R TR-85-33 %D DEC 1985 %I University of Texas at Austin Department of Computer Sciences %K AI07 AI04 %X "The Critter is an artificial creature which learns, not only the structure of its (simulated) environment, but also the interpretation of the actions and senses that give it access to that environment." %A Newton S. Lee %A John W. Roach %T Guess/1: A General Purpose Expert Systems Shell %R 85-3 %I Virginia Tech Computer Science Department %K T03 %A John W. Roach %A Glenn Fowler %T Virginia Tech Prolog/Lisp A Dual Interpeter Implementation %R 85-18 %I Virginia Tech Computer Science Department %K T01 T02 %A J. Patrick Bizler %A Layne T. Watson %A J. Patrick Sanford %T Spline Based Recognition of Straight Lines and Curves in Engineering Line Drawing %R 85-29 %I Virginia Tech Computer Science Department %K AI06 AA05 %A Richard E. Nance %A Robert L. Moose %A Robert V. Foutz %T A Statistical Technique for Comparing Strategies: An Example from Computer Network Design %R 85-26 %I Virginia Tech Computer Science Department %K O04 AA08 AI09 anova %A T. C. Hu %A M. T. Shing %T The Alpha-Beta Routing %R TRCS85-08 %I University of California, Santa Barbara %K AA05 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 06:52:58 1986 Date: Thu, 5 Jun 86 06:52:53 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #140 Status: RO AIList Digest Wednesday, 4 Jun 1986 Volume 4 : Issue 140 Today's Topics: Literature - Technical Reports #2 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Technical Reports #2 %A M. A. Fulk %T A Study of Inductive Inference Machines %R 85-10 %D August 1985 %I SUNY Buffalo Computer Science %K AI04 %X Inductive inference machines (IIMs) model learning and scientific theory formation. We investigate IIMs that attempt to synthesize (in the limit) a program for a function as they receive data (in the form of input-output pairs) about that function. We show that a postdictively consistent IIM can be effectively replaced with a postdictively complete IIM that succeeds on all of the functions that the original did. We also investigate IIMs that attempt to synthesize (again in the limit) a program that enumerates an r.e. set as they receive data consisting of the elements of that set. Finally, we propose new criteria for success in inductive inference. %R 85-11 %A J. S. Royer %T A connotational theory of program structure %D September 1985 %I SUNY Buffalo Computer Science %K AA08 %R 85-12 %T Local symmetry computation for shape description %A G. W. Lee %A S. N. Srihari %D September 1985 %I SUNY Buffalo Computer Science %K AI06 %R 85-13 %T ROCS: A system for reading off-line cursive script %A R. M. Bo\o'z\(hc'inovi\o'c\(aa' %A S. N. Srihari %D September 1985 %I SUNY Buffalo Computer Science %K AI06 %R UMCS-85-8-1 %A David E. Rydeheard %A Rod M. Burstall %T The Unification of Terms: A Category-Theoretic Algorithm %I The University of Manchester, Department of Computer Science %K AI11 %X no charge As an illustration of the role of abstract mathematics in program design, an algorithm for the unification of terms is derived from constructions of colimits in category theory. %A Trevor P. Hopkins %R UMCS-85-9-2 %T Image Transfer by Packet-switched Network %I The University of Manchester, Department of Computer Science %K AI06 %X no charge The advantages and disadvantages of using packet-switching technology for the transfer of image information in real time are considered. An experimental implementation of parts of a system based on a high-speed Local Area Network is described; these include a simple screen output device and a real-time camera input device. The generation of images using a number of microprocessors is also described. A number of applications for such a system are investigated and the extension of this approach to implement an Integrated Information Presentation system is considered. %A Howard Barringer %R UMCS-85-9-3 %T Up and Down the Temporal Way %I The University of Manchester, Department of Computer Science %K AA08 elevator %X no charge A formal specification of a multiple lift system is constructed. The example illustrates and justifies one of many possible system specification styles based on temporal techniques. %A Ru-qian Lu %T Expert Union: United Service of Distributed Expert Systems %R 85-3 %I University of Minnesota-Duluth %C Duluth, Minnesota %D June, 1985 %K AI01 H03 %X A scheme for connecting expert systems in a network called an {\nit expert union} is described. Consultation scheduling algorithms used to select the appropriate expert(s) to solve problems are proposed, as are strategies for resolving contradictions. %R No 27 %T The Complexity of a Translation of L-calculus to Categorical Combinators %A R D Lins %D April 1985 %I University of Kent at Canterbury %A Sheldon Klein %T The Invention of Computationally Plausible Knowledge Systems in the Upper Paleolithic %D December 1985 %R TR 628 %I Computer Sciences Department, University of Wisconsin %C Madison, WI %K AI08 %X Abstract: The problem of computing human behavior by rules can become intractable with large scale knowledge systems if the human brain, like a computer, is a finite state automaton. The problem of making such computations at a pace fast enough for ordinary social interaction can be solved if appropriate constraints apply to the structure of those rules. There is evidence that systems of such constraints were invented in the Upper Paleolithic, and were of sufficient power to guarantee that the time necessary for computation of behavior would increase only linearly with increases in the size and heterogeneity of world knowledge systems. Fundamentally, there was just one type of computational invention, capable of unifying the full range of human sensory domains, and consisting of an analogical reasoning method in combination with a global classification scheme. The invention may have been responsible for the elaboration of language and culture structures in a process of co-evolution. The encoding of the analogical mechanism in iconic visual imagery and myth structures may have given rise to the phenomenon of Shamanism. The theory is testable, and one of its implications is that the structuralism of Levi-Strauss has an empirical foundation. %A G.T. NGUYEN %A J. OLIVARES %D JAN 1985 %R IMAG RR TIGRE 26 %C Grenoble, France %T SYCSLOG - systeme logique d'integrite semantique %A M. ADIBA %A Q.N. BUI %A J. PALAZZO DE OLIVEIRA %D JAN 1985 %R IMAG RR TIGRE 23 %C Grenoble, France %T Notion de temps dans les bases de donnees generalisees %A A. DANDACHE %D APR 1985 %R IMAG RR 516 %C Grenoble, France %T Etude de structures regulieres PLA - ROM dans la partie controle de microprocesseurs %A S. GRAF %A J. SIFAKIS %D FEB 1985 %R IMAG RR 526 %C Grenoble, France %T From synchronization tree logic to acceptance model logic %A H. BALACHEFF %D MAY 1985 %R IMAG RR 528 %C Grenoble, France %T Processus de preuves et situations de validation %A Michel COSNARD %A Yves ROBERT %A Denis TRYSTRAM %D JUL 1985 %R IMAG RR 552 %C Grenoble, France %T Resolution parallele de systemes lineaires denses par diagonalisation %K AI11 %A Yves ROBERT %A Denis TRYSTRAM %D JUL 1985 %R IMAG RR 553 %C Grenoble, France %T Un reseau systolique orthogonal pour le probleme du chemin algebrique %A J.R. BARRA %A M. BECKER %A D. BELAID %A F. CHATELIN %A C. MAZEL %D JUN 1985 %R IMAG RR 542 %C Grenoble, France %T Realisation d'un logiciel d'analyses factorielles avec systeme d'assistance intelligente a l'utilisateur %A Jean FONLUPT %A Denis NADDEF %D SEP 1985 %R IMAG RR 557 %C Grenoble, France %T The traveling salesman problem in graphs with some excluded minors %A Yves DEMAZEAU %D APR 1985 %R IMAG RR 502 %C Grenoble, France %T La programmation des jeux: programmation classique et intelligence artificielle %K AA17 %A Hicham AL NACHAWATI %D 1985 %I These Universite, GRENOBLE %K SEGMENTATION %K PROCESSUS ARBORESCENT %K ANALYSE VARIANCE %K CLASSIFICATION AUTOMATIQUE %T Processus de classification sequentiels non arborescents pour l'aide au diagnostic %W IMAG Mediatheque %A Xin an PAN %D 1985 %I These Universite, GRENOBLE %K MINIMA %K ALGORITHME ITERATIF %K RESEAU AUTOMATE %K AUTOMATE %K RECONNAISSANCE CARACTERE %K DISTANCE %T Experimentation d'automates a seuil pour la reconnaissance de caracteres %W IMAG Mediatheque %A Laurent BERGHER %D 1985 %I These doct. ing., GRENOBLE %K ANALYSE %K POTENTIEL %K VLSI %K MICROPROCESSEUR %K ANALYSE IMAGE %K TEST %K CAPTEUR IMAGE %T Analyse de defaillances de circuits VLSI par microscopie electronique a balayage %W IMAG Mediatheque %A Philippe VIGNARD %D 1985 %I These doct. ing., GRENOBLE %K REPRESENTATION CONNAISSANCE %K EXPLOITATION %K FILTRAGE %K DISTRIBUTION %K SEMANTIQUE %K ANALOGIE %K TYPOLOGIE %T Un mecanisme d'exploitation a base de filtrage flou pour une representation des connaissances centree objets %W IMAG Mediatheque %A Prabhaker Mateti %T Correctness Proof of an Indenting Program %R Technical Report 80/2 %I Department of Computer Science, University of Melbourne %D September 1980 %P 59 %K verification, correctness proof, pretty printing, pascal %O also in Software - Practice and Experience %K AA08 %X The correctness of an indenting program for Pascal is proven at an intermediate level of rigour. The specifications of the program are given in the companion paper [TR 80/1]. The program is approximately 330 lines long and consists of four modules: io, lex, stack, and indent. We prove first that the individual procedures contained in these modules meet their specifications as given by the entry and exit assertions. A global proof of the main routine then establishes that the interaction between modules is such that the main routine meets the specification of the entire program. We argue that correctness proofs at the level of rigour used here serve very well to transfer one's understanding of a program to others. We believe that proofs at this level should become commonplace before more formal proofs can take over to reduce traditional testing to an inconsequential place. %A Joxan Jaffa %T Presburger Arithmetic with Array Segments %R Technical Report 81/1 %I Department of Computer Science, University of Melbourne %D January 1981 %P 8 %K verification, assertion language, decision procedure AA08 %A John W. Lloyd %T An Introduction to Deductive Database Systems %R Technical Report 81/3 %I Department of Computer Science, University of Melbourne %D April 1981 (revised April 1983) %P 24 %K T02 AA14 AA09 %O also in Australian Computer Journal, vol.15, 1983 %X This paper gives a tutorial introduction to deductive database systems. Such systems have developed largely from the combined application of the ideas of logic programming and relational databases. The elegant theoretical framework for deductive database systems is provided by first order logic. Logic is used as a uniform language for data, programs, queries, views and integrity constraints. It is stressed that it is possible to build practical and efficient database systems using these ideas. %A John W. Lloyd %T Implementing Clause Indexing for Deductive Database Systems %R Technical Report 81/4 %I Department of Computer Science, University of Melbourne %D October 1981 %P 22 %K AA14 AA09 %X The paper presents a file design for handling partial-match queries which has wide application to knowledge-based artificial intelligence systems and relational database systems. The advantages of the design are simplicity of implementation, the ability to cope with dynamic files and the ability to optimize performance with respect to the average number of disk access required to answer a query. %A Joxan Jaffar %A Jean-Louis Lassez %T A Decision Procedure for Theorems about Multisets %R Technical Report 81/7 %I Department of Computer Science, University of Melbourne %D July 1981 %P 37 %K automatic theorem proving, verification, domain dependent reasoning AI11 AA13 %A Lee Naish %T An Introduction to MU-Prolog %R Technical Report 82/2 %I Department of Computer Science, University of Melbourne %D March 1982 (Revised July 1983) %P 16 %K T02 muprolog AI10 control negation %X As a logic programming language, PROLOG is deficient in two areas: negation and control facilities. Unsoundly implemented negation affects the correctness of programs and poor control facilities affect the termination and efficiency. These problems are illustrated by examples. MU-PROLOG is then introduced. It implements negation soundly and has more control facilities. Control information can be added automatically. This can be used to avoid infinite loops and find efficient algorithms from simple logic. MU-PROLOG is closer to the ideal of logic programming. %A Joseph Stoegerer %T Specification Languages - A Survey %R Technical Report 82/5 %I Department of Computer Science, University of Melbourne %D June 1982 %P 62 %K software specification, requirements languages, software development tools, integrated software development support systems, non-procedural languages, automated analysis tools AA08 %A Joxan Jaffar %A Jean-Louis Lassez %A John W. Lloyd %T Completeness of the Negation-as-failure Rule %R Technical Report 83/1 %I Department of Computer Science, University of Melbourne %D January 1983 %P 20 %O also in Proceedings of the Eigth International Joint Conference on Artificial Intelligence, Karlsruhe, Germany, 1983 %K AI10 finite failure, completion of a program %X Let P be a Horn clause logic program and comp(P) be its completion in the sense of Clark. Clark gave a justification for the negation as failure rule by showing that if a ground atom A is in the finite failure set of P, then ~A is a logical consequence of comp(P), that is, the negation as failure rule is sound. We prove here that the converse also holds, that is, the negation as failure rule is complete. %A Jean-Louis Lassez %A Michael J. Maher %T Closures and Fairness in the Semantics of Logic Programming %R Technical Report 83/3 %I Department of Computer Science, University of Melbourne %D March 1983 %P 17 %K semantics, chaotic iteration, SLD resolution, finite failure, T92 %O also in Theoretical Computer Science, vol.29, 1984 %A Jean-Louis Lassez %A Michael J. Maher %T Optimal Fixedpoints of Logic Programming %R Technical Report 83/4 %I Department of Computer Science, University of Melbourne %D March 1983 %P 15 %K theory, semantics AA08 AI10 %O also in Theoretical Computer Science, vol.30, 1985 %X From a declarative programming point of view, Manna and Shamir's optimal fixedpoint semantics is more appealing than the least fixedpoint semantics. However in standard formalisms of recursive programming the optimal fixedpoint is not computable while the least fixedpoint is. In the context of logic programming we show that the optimal fixedpoint is equal to the least fixedpoint and is computable. Furthermore the optimal fixedpoint semantics is consistent with Van Emden and Kowalski's semantics of logic programs. %A Lee Naish %T Automatic Generation of Control for Logic Programming %R Technical Report 83/6 %I Department of Computer Science, University of Melbourne %D July 1983 (Revised September 1984) %P 24 %K T02 O02 muprolog, control facilities, coroutines, automatic programming %O also as Automating Control for Logic Programs'' in Journal of Logic Progrmm ing, vol.5, 1985 %X A model for the coroutined execution of PROLOG programs is presented and two control primitives are described. Heuristics for the control of database and recursive procedures are given, which lead to algorithms for generating control information. These algorithms can be incorporated into a pre-processor for logic programs. It is argued that automatic generation should be an important consideration when designing control primitives and is a significant step towards simplifying the task of programming. %A Lee Naish %A James A. Thom %T The MU-Prolog Deductive Database %R Technical Report 83/10 %I Department of Computer Science, University of Melbourne %D November 1983 %P 16 %K muprolog, partial match retrieval, unix T02 AA09 AA14 %X This paper describes the implementation and an application of a deductive database being developed at the University of Melbourne. The system is implemented by adding a partial match retrieval system to the MU-PROLOG interpreter. %A David A. Wolfram %A Jean-Louis Lassez %A Michael J. Maher %T A Unified Treament of Resolution Strategies for Logic Programs %R Technical Report 83/12 %I Department of Computer Science, University of Melbourne %D December 1983 %P 25 %K soundness, completeness, unification, negation as failure AI10 %O also in Proceedings of the Second International Logic Programming Conference, Uppsala, Sweden, 1984 %A Lee Naish %T Heterogeneous SLD Resolution %R Technical Report 84/1 %I Department of Computer Science, University of Melbourne %D January 1984 %P 11 %K T02 AI10 resolution, control facilities, intelligent backtracking %O also in Journal of Logic Programming, vol.4, 1984 %X Due to a significant oversight in the definition of computation rules, the current theory of SLD resolution is not general enough to model the behaviour of some PROLOG implementations with advanced control facilities. In this paper, Heterogeneous SLD resolution is defined. It is an extension of SLD resolution which increases the \*(lqdon't care\*(rq non-determinism of computation rules and can decrease the size of the search space. Soundness and completeness, for success and finite failure, are proved using similar results from SLD resolution. Though Heterogeneous SLD resolution was originally devised to model current systems, it can be exploited more fully than it is now. As an example, an interesting new computation rule is described. It can be seen as a simple form of intelligent backtracking with few overheads. %A Koenraad Lecot %A Isaac Balbin %T Prolog & Logic Programming Bibliography %R Technical Report 84/3 %I Department of Computer Science, University of Melbourne %D May 1984 %P 55 %K classified bibliography AT21 T02 AI10 %O a considerably expanded version appeared as Logic Programming: A Classified Bibliography'', Wildgrass Books, 1985 %A Lee Naish %T All Solutions Predicates in Prolog %R Technical Report 84/4 %I Department of Computer Science, University of Melbourne %D June 1984 %P 15 %K logic programming, negation, coroutines T02 AI10 %O also in Proceedings of IEEE Symposium on Logic Programming, Boston, 1985 %A Michael J. Maher %A Jean-Louis Lassez %A Kmball G. Marriott %T Antiunification %R Technical Report 84/5 %I Department of Computer Science, University of Melbourne %D to appear %P ? %K AI10 unification %A Lee Naish %A Jean-Louis Lassez %T Most Specific Logic Programs %R Technical Report 84/6 %I Department of Computer Science, University of Melbourne %D to appear %P ? %K AI10 %A Rodney W. Topor %A Teresa Keddis %A Derek W. Wright %T Deductive Database Tools %R Technical Report 84/7 %I Department of Computer Science, University of Melbourne %D June 1984 (revised August 1985) %P 27 %K database management, deductive database, query language, integrity constraint, logic programming, T02 AA14 AA09 T02 AI10 %O also in Australian Computer Journal, vol.?, 1985 %X A deductive database is a database in which data can be represented both explicitly by facts and implicitly by general rules. The use of typed first order logic as a definition and manipulation language for such deductive databases is advocated and illustrated by examples. Such a language has a well-understood theory and provides a uniform notation for data, queries, integrity constraints, views and programs. We present algorithms for implementing domains, for using atoms with named attributes, for evaluating queries, and for checking static and transition integrity constraints. The implementation is by translation into Prolog and can be performed using a standard Prolog system. The paper assumes some familiarity with relational databases, logic and Prolog. %R CSL T.R. 85-281 %T Prolog Memory-Referencing Behavior %A Evan Tick %D September 1985 %K T02 %I Computer Systems Laboratory, Stanford University %X This report describes Prolog data and instruction memory-referenci ng characteristics. Prolog exhibits unconventional referencing behavior of backtracking; the saving and subsequent restoration of a program state. Backtracking introduces memory bandwidth requirements above those of procedural languages. The significance of this and other characteristics was measured by emulating a Prolog architecture running three benchmark programs and simulating various memory models. The results indicate that so-called determinate programs require substantial memory bandwidth because of a limited form of backtracking (shallow). However, this referencing behavior exhibits spatial locality enabling small memory buffers to reduce the bandwidth requirement. A modification to the Prolog architecture having the advantage of further increasing locality is described. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 06:53:55 1986 Date: Thu, 5 Jun 86 06:53:50 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #141 Status: RO AIList Digest Thursday, 5 Jun 1986 Volume 4 : Issue 141 Today's Topics: Seminars - Synchronizing Plans among Intelligent Agents (SRI) & Model-Based Reasoning with Causal Ordering (CMU) & Tree Adjoining Grammars (UPenn) & Connectionist Expert Systems (GTE) & Knowledge-Based Design & Qualitative Process Theory (SU) & FP Rewrite Rules & Parallel Unification (IBM-SJ), Seminar Series - CSMIL (UMich), Conference - Call for Papers for IJCAI-87 ---------------------------------------------------------------------- Date: Wed 28 May 86 14:31:47-PDT From: Amy Lansky Subject: Seminar - Synchronizing Plans among Intelligent Agents (SRI) SYNCHRONIZING PLANS AMONG INTELLIGENT AGENTS VIA COMMUNICATION Charlie Koo (KOO@SUSHI) Stanford University 11:00 AM, MONDAY, June 2 SRI International, Building E, Room EJ228 (new conference room) In a society where a group of agents cooperate to achieve certain goals, the group members perform their tasks based on certain plans. Some tasks may interact with tasks done by other agents. One way to coordinate the tasks is to let a master planner generate a plan and distribute tasks to individual agents accordingly. However, there are two difficulties. Firstly, the master planner needs to know all the expertise that each agent has. The amount of knowledge sharply increases with the number of specialties. Secondly, the master-planning process will be computationally more expensive than if each agent plans for itself, since the planning space for the former is much larger. Therefore, distributed planning is motivated. The objective of this on-going research is to formalize a model for synchronizing and monitoring plans independently made by nonhostile intelligent agents via communication. The proposed model also will provide means to monitor the progress of plan execution, to prevent delays, and to modify plans with less effort when delays happen. In this talk, a commitment-based communication model which allows agents to track their commitments during execution of plans will be proposed. It includes a language, a set of communication operators and a set of commitment tracking operators. The process of synchronizing plans based on this communication model will also be described. Relevant work: Contract Net, nonlinear planners, distributed planners. ------------------------------ Date: 28 May 1986 1217-EDT From: Yumi Iwasaki Subject: Seminar - Model-Based Reasoning with Causal Ordering (CMU) I will be presenting my thesis proposal as follows: Date : Tuesday, June 3, 1986 Time : 2 pm Place : WeH 5409 Title : Model-Based Reasoning of Device Behavior with Causal Ordering Causality plays an important role in human understanding of the world. While a number of artificial intelligence systems have been built that reason with causal knowledge, few have addressed the issue of not only representing and using causal knowledge but also of discovering causal relations in the domain based on an operational definition of causality. We propose to study discovering, representing, and using causal knowledge based on the definition of causal relations given by the theory of causal ordering. The proposed scheme for causal reasoning has several levels of representation of knowledge, namely the network representation of processes, equation model of components, and causal ordering structure. The scheme links the knowledge at the level of intuitive understanding of processes to the diagnostic level via an intermediate, more formal model represented as a system of equations. In this research, we will study application of the concept of causal ordering to a task of reasoning about physical device behavior by implementing a causal reasoning program, ACORD, in the domain of a coal power plant. We also expect to contribute to better understanding of advantages and disadvantages of model-based and evidential reasoning. ------------------------------ Date: Mon, 2 Jun 86 21:53 EDT From: Tim Finin Subject: Seminar - Tree Adjoining Grammars (UPenn) A STUDY OF TREE ADJOINING GRAMMARS Vijayshanker Ph.D. dissertation proposal 1:30pm June 9, 1986; Room 337, Towne Building The goal of this research is to study a grammatical formalism called Tree Adjoining Grammars (TAG's). The original motivation for TAG's was linguistic and subsequent work established their linguistic relevance. Our study consists of two parts. The first part deals with formal properties of TAG's: for example, closure properties ; automaton characterizing classes of string languages and tree languages generated by TAG's. In the second part of our study, we outline how a syntax driven scheme for providing compositional semantics of natural languages can be given with the Tree Adjoining Grammars. Committee: J. H. Gallier A. K. Joshi (Supervisor) A. Kroch R. Larson (MIT) W. Rounds (U of Michigan, Ann Arbor) B. L. Webber (Chairperson) ------------------------------ Date: Wed, 4 Jun 86 11:18:18 edt From: Rich Sutton Subject: Seminar - Connectionist Expert Systems (GTE) "Connectionist Expert Systems in a Noisy World" by Stephen I. Gallant This talk will describe a model for connectionist expert systems (MACIE) and show how it is well suited to noisy and redundant environments. Connectionist expert systems are diagnostic expert systems based upon a connectionist model with several interesting features: -- They can be generated from training examples (and/or rules) -- They perform forward chaining to make conclusions and backward chaining to elicit additional information -- They give IF-THEN rules to justify their inferences, even though their knowledge base contains no such rules -- They are arguably less prone to brittle behavior than traditional expert systems. In the talk it will be shown how an expert system for a noisy and redundant problem can be constructed from: (1) a noise-free model of an underlying process (perhaps a traditional expert system) and (2) a model for the noise involved. System generation is entirely automated. Where: GTE Labs, Waltham, MA When: June 11th, 9:30 am Contact: Rich Sutton, rich@gte-labs.csnet, 617-466-4133 (or 466-4207) Net address of speaker: sig@northeastern Also: That afternoon we will have an informal research meeting of connectionists from GTE, UMass, and Northeastern Welcome: Visitors are welcome! ------------------------------ Date: Wed 4 Jun 86 10:58:14-PDT From: Christine Pasley Subject: Seminars - Knowledge-Based Design & Qualitative Process Theory (SU) CS529 - AI In Design & Manufacturing Instructor: Dr. J. M. Tenenbaum Speaker: Sanjay Mittal From: Xerox Palo Alto Research Center Title: Pride: A Knowledge-Based Framework for Design Guest Speaker: Kenneth Forbus From: Qualitative Reasoning Group University of Illinois Title: Qualitative Process Theory: Selected Topics Date: Wednesday, June 4, 1986 Time: 4:00 - 5:30 Place: Terman 556 Sanjay Mittal's abstract: This talk will describe the Pride project at Xerox. The first part of the talk will be about an expert system for the design of paper transports inside copiers. A prototype version of the system has been in field test for a year. It has been successfully used on real copier projects inside Xerox - both for designing and for checking designs produced by engineers. From an applications point of view we have been motivated by the following observations: knowledge is often distributed among different experts; the process of generating designs is unnecessarily separated from their analysis, leading to long design cycles; and design is an evolutionary process, i.e., a process of exploration. The second part of the talk will describe the framework in Pride for representing design knowledge and using it to support the design process. In this framework, the process of designing an artifact is viewed as knowledge guided search in a multi-dimensional space of possible designs. The dimensions of such a space are the design parameters of the artifact. In this view, knowledge is used not only to search the space but also to define the space. Domain knowledge is organized in terms of design plans, which are organized around goals. Conceptually, goals decompose a problem into sub-problems and are the units for structuring knowledge. Design goals have design methods associated with them, which specify alternate ways to make decisions about the design parameters of the goal. The third major element of a plan are constraints on the design parameters. The framework provides a problem solver for executing these plans. The problem solver extends dependency-directed backtracking with an advice mechanism and a context mechanism for simultaneously maintaining multiple designs. Kenneth Forbus' abstract: Much of our commonsense knowledge of the physical world appears to be organized around a notion of physical processes. Qualitative Process theory provides a formal language for describing such processes, including a qualitative representation of differential equations and the conditions under which they apply. This talk will briefly review Qualitative Process theory and discuss two topics of current research: Interpreting measurements taken across time, and a new implementation, based on an assumption-based truth maintenance system, that provides roughly two orders of magnitude performance improvement. ------------------------------ Date: Wed, 04 Jun 86 17:46:49 PDT From: Almaden Research Center Calendar Subject: Seminars - FP Rewrite Rules & Parallel Unification (IBM-SJ) IBM Almaden Research Center 650 Harry Road San Jose, CA 95120-6099 RESEARCH CALENDAR June 9 - 13, 1986 GOOD REWRITE STRATEGIES FOR FP E. Wimmers, IBM Almaden Research Center Computer Science Seminar Wednesday, June 11 2:30 P.M. Room: B2-307 In order to implement a language based on rewrite rules, it does not suffice to know that there are enough rules in the language; we also need to have a good strategy for determining the order in which to apply them. But what is good? Corresponding to each notion of having enough rules, there is a corresponding notion of a good rewrite strategy. We examine and characterize these notions of goodness, and give examples of a number of natural good strategies. Although we have confined ourselves to FP here, we believe that our techniques (some of which are nontrivial extensions of techniques first used in the context of lambda-calculus) will apply well beyond the realm of FP rewriting systems. Host: J. Backus ... ON THE PARALLEL COMPLEXITY OF UNIFICATION OF TERMS AND RELATED PROBLEMS C. Dwork, IBM Almaden Research Center Comp. Sci. Colloquium Thursday, June 12 3:00 P.M. Room: Rear Audit. Unification of terms is a well known problem with applications to a variety of symbolic computation problems. Two terms s and t, involving function symbols and variables, are unifiable if there is a substitution for the variables under which s and t become syntactically identical. For example, f(x,x) and f(g(y),g(g(c))) are unified by substituting g(c) for y and g(g(c)) for x. As parallel architectures become technologically feasible, researchers in logic programming have sought parallel unification algorithms running at speeds subpolynomial in the length of the input. Unfortunately, the existence of such an algorithm has been shown to be "popularly unlikely," in that it would violate commonly held beliefs about the structure of the class P of problems solvable in polynomial time. Two special cases of unification are term matching and equivalence testing, in which one or both of the terms contain no variables, respectively. In contrast to the case for general unification, term matching and testing for equivalence can both be solved deterministically in time O((log n)**2) for inputs of size n, using M(n**2) processors, where M(k) is the number of sequential operations needed to multiply k-by-k matrices (roughly k**2.5). The processor bound can be improved to M(k) if randomization is allowed. This is joint work with Paris Kanellakis and Larry Stockmeyer. Host: R. Strong ... ------------------------------ Date: Sun, 1 Jun 86 20:20:38 EDT From: Gary_M._Olson%UMich-MTS.Mailnet@MIT-MULTICS.ARPA Subject: Seminar Series - CSMIL (UMich) The Cognitive Science and Machine Intelligence Laboratory (CSMIL) at the University of Michigan has been conducting a major lecture series this spring, consisting of the following speakers: March 31 -- John Anderson, Carnegie-Mellon April 21 -- Shimon Ullman, M.I.T. May 5 -- Allen Newell, Carnegie-Mellon May 12 -- Bobby Inman, M.C.C. May 19 -- Roger Schank, Yale June 24 -- Randy Davis, M.I.T. Anyone interested in further information should contact: Gary Olson, Director Cognitive Science and Machine Intelligence Laboratory University of Michigan 904 Monroe Street Ann Arbor, Michigan 48109 313-747-4948 net address: Gary_Olson%UMich-MTS.Mailnet@MIT-Multics.Arpa ------------------------------ Date: Wed, 4 Jun 86 23:09:06 edt From: walker@mouton.bellcore.com (Don Walker) Subject: Conference - Call for Papers for IJCAI-87 CALL FOR PAPERS: IJCAI-87 Tenth International Joint Conference on Artificial Intelligence August 23-28, 1987 Milan, Italy The IJCAI conferences are the main forums for the presentation of artificial intelligence research to an international audience. The goal of IJCAI-87 is to promote scientific interchange, within and between all subfields of AI, among researchers from all over the world. The conference is sponsored by the International Joint Conferences on Artificial Intelligence, Inc. (IJCAII). In response to the growing interest in engineering issues within the AI community, IJCAI-87's Technical Program will have two distinct tracks: science and engineering. The science papers, presented Sunday through Wednesday (August 23-26), will stress the computational principles underlying cognition and perception in man and machine. The engineering papers, presented Tuesday through Friday (August 25-28), will highlight pragmatic issues that arise in applying these computational principles. Tutorials will be presented on Sunday and Monday in parallel with the first two days of the science paper presentations. Meetings or workshops focussed on specific research issues might most appropriately be held on Thursday or Friday. TOPICS OF INTEREST Authors are invited to submit papers to either the science or engineering tracks within one of the following topic areas: - Architectures and Languages (including logic programming, user interface technology) - Reasoning (including theorem proving, planning, explaining) - Knowledge Acquisition and Learning (including knowledge-base maintenance) - Knowledge Representation (including task domain analysis) - Cognitive Modeling - Natural Language Understanding - Perception and Signal Understanding (including speech, vision, data interpretation) - Robotics REQUIREMENTS FOR SUBMISSION: Authors are requested to prepare full papers, no more than 7 proceedings' pages (approximately 5600 words), or short papers, no more than 3 proceedings' pages (approximately 2400 words). The full-paper classification is intended for well-developed ideas, with significant demonstration of validity, while the short-paper classification is intended for descriptions of research in progress. Authors must ensure that their papers describe original contributions to or novel applications of AI, regardless of length classification, and that the research is properly compared and contrasted with relevant literature. DETAILS OF SUBMISSION: Authors should submit six (6) copies of their papers (hard copy only -- we cannot accept on-line files) to the Program Chair no later than Monday, January 5, 1987. The following information must be included on the title page: - Author's name, address, telephone number and computer mail address (if applicable) - Paper type (full-paper or short-paper), topic area, track (science or engineering), and a few keywords for further classification within the topic area - An abstract of 100-200 words The timetable is as follows: - Submission deadline: 5 January 1987 (papers received after January 5 will be returned unopened) - Notification of acceptance or rejection: 17 March 1987 - Camera ready copy due: 10 April 1987 The language of the conference is English; all papers submitted should be written in English. REVIEW CRITERIA: Each paper will be reviewed by at least two experts. Acceptance will be based on the overall merit and significance of the reported research, as well as on the quality of the presentation. A paper may be reviewed by experts responsible for an area or track other than the one to which it was submitted if, in the opinion of a program committee member, it can thereby be more fairly reviewed. Papers submitted to the science track should make an original and significant contribution to knowledge in the field of artificial intelligence. Papers submitted to the engineering track should focus on pragmatic issues that arise in reducing AI principles and techniques to practice. Such papers could identify the critical features of some successful application system's approach to reasoning or knowledge acquisition or natural language understanding. Of particular interest are papers that demonstrate insightful analysis of a task domain motivating the selection of a computational and representational approach. CONTACT POINTS: Submissions and inquiries about the program should be sent to the Program Chair: John McDermott Department of Computer Science Carnegie-Mellon University Pittsburgh, PA 15213 USA 1-412-268-2599 McDermott@cmu-cs-a.arpa Inquiries about registration, tutorials, exhibits, and other local arrangements should be sent to the Local Arrangements Chair: Marco Somalvico Dipartimento di Elettronica Politecnico di Milano Piazza Leonardo Da Vinci N.32 I-20133 Milano ITALY 39-2-236-7241 somalvic!prlb2@seismo Other inquiries should be directed to the General Chair: Alan Bundy Department of Artificial Intelligence University of Edinburgh 80 South Bridge Edinburgh EH1 1HN UK 44-31-225-7774 ext 242 Bundy%edinburgh.ac.uk@ucl-cs.arpa ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 19:00:23 1986 Date: Thu, 5 Jun 86 19:00:13 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #142 Status: R AIList Digest Thursday, 5 Jun 1986 Volume 4 : Issue 142 Today's Topics: Queries - Getting Started with OPS-5 & Programming Paradigms & Prolog on IBM/PCs, Techniques - Common LISP Style, Physics - Space-Time Structure, Humor - Brain Theory, Philosophy - Metaphilosophy Journal on Computer Ethics ---------------------------------------------------------------------- Date: 3 Jun 86 18:18:38 GMT From: cad!nike!lll-crg!micropro!ptsfa!jeg@ucbvax.berkeley.edu (John Girard) Subject: Getting Started with OPS-5 We would like to start experimenting with OPS-5, and have heard that there is a public domain version available, presumably from C-M-U. Any help we can get on the following would be appreciated: Where is the best source for the P-D OPS-5? Would we be wasting our time to try the P-D version? If so, which one can we try on an evaluation basis? What else is needed to make it work? If LISP is required, can we operate on a limited subset such as XLISP? If not, what LISP would be easiest to integrate on an evaluation basis? Also, any recommendations on readable and usable guides to OPS-5 will be appreciated! Thanks! John Girard Pacific Bell (415)823-1961 [USA] {dual,ihnp4,qantel,decwrl,bellcore}ptsfa!jeg ------------------------------ Date: 3 Jun 86 12:42:33 GMT From: ulysses!unc!mcnc!duke!jds@ucbvax.berkeley.edu (Joseph D. Sloan) Subject: Request for Programming Paradigms A particular interest of mine is programming paradigms. For example, how does object-oriented programming differ from logic programming from functional programming from procedural programming from ... I recently came across a paper with a brief discussion of access-oriented programming which is a new paradigm to me. Unfortunately, I didn't very much out of the description as the context of the article was comparison of paradigms and really assumed familiarity. Can anyone supply me with pointers to readable introductions to access-oriented programming? How about articles or books on programming paradigms in general? Reply by mail and I will summarize results if there is enough interest. (The article I referred to was "If Prolog is the Answer, What is the Question? or What it Takes to Support AI Programming Paradigms" by Daniel G. Bobrow in IEEE Trans. of Soft. Eng., Nov. 1985. I recommend the article.) Joe Sloan, Box 3090 Duke University Medical Center Durham, NC 27710 (919) 684-3754 duke!jds, ------------------------------ Date: 3 Jun 86 14:46:53 GMT From: sdcsvax!caip!seismo!columbia!lexington.columbia.edu!polish@ucbvax .berkeley.edu (Nathaniel Polish) Subject: Prolog on IBM/PCs I am looking for a version of Prolog (or other expert system building tool) for the IBM/PC environment. I am looking for comments on the real usefulness of these tools. Thanks Nat Polish@columbia-20 ------------------------------ Date: 3 Jun 86 19:41:30 GMT From: hplabs!oliveb!glacier!kestrel!king@ucbvax.berkeley.edu (Dick King) Subject: Re: Common LISP style standards. From: michaelm@bcsaic.UUCP (michael maxwell) We have a long list, and we wish to apply some test to each member of the list. However, at some point in the list, if the test returns a certain value, there is no need to look further ... I'm way behind in this group, so I apologize in advance if you have seen this solution or a better one before. You might try (prog () (mapcar #'(lambda (y) (when (you-like y) (return (result-for y)))) x))) I tried it, and it works. It doesn't seem dirty to me, and it should be efficient. Even if the return point of a prog is such that it forces the lexical closure to be non-vacuous, this shouldn't be a problem when compiled. -- Mike Maxwell Boeing Artificial Intelligence Center ...uw-beaver!uw-june!bcsaic!michaelm -dick ------------------------------ Date: Wed, 4 Jun 86 09:34:08 pdt From: Marc Majka Subject: Inside Out > ...Einstein's theory of general relativity, which models the cosmos > as a 4 dimensional pseudo-Riemannian spacetime. ... *pseudo*-Riemannian? I think you mean Semi-Reimannian, and that applies to the metric, not the spacetime. --- Marc Majka ------------------------------ Date: 4 Jun 86 06:29 EDT From: WAnderson.wbst@Xerox.COM Subject: Humor - Brain Theory Conscious and subconscious mind: In your brain are two files. One is read-write. The other is write-only with global side effects. (Attributed to a computer science student at Rochester Institute of Technology.) Bill Anderson ------------------------------ Date: Tue, 27 May 86 13:36:39 edt From: rti-sel!dg_rtp!rtp41!dg_rama!bruces%mcnc.csnet@CSNET-RELAY.ARPA Subject: Computer Ethics [Forwarded from the Risks Digest by Laws@SRI-AI.] The following is a copy of a review I wrote for a recent newsletter of the Boston chapter of Computer Professionals for Social Responsibility (CPSR). Readers of RISKS may be interested, as well. METAPHILOSOPHY is a British journal published three times yearly which is dedicated to considerations about particular schools, fields, and methods of philosophy. The October 1985 issue, Computers & Ethics (Volume No. 16, Issue No. 4), is recommended reading [...]. This issue's articles attempt to define and delimit the scope of Computer Ethics, and examine several emerging and current concerns within the field. One current concern is responsibility for computer-based errors. In his article on the subject, John W. Snapper asks: "...whether it is advisable to ...write the law so that a machine is held legally liable for harm." The author invokes Aristotle's "Nichomachean Ethics" (!) in an analysis of how computers make decisions, and what is meant by "decision" in this context. On the same subject, William Bechtel goes one step further, considering the possibility that computers could one day bear not only legal, but moral responsibility for decision-making: "When we have computer systems that ...can be embedded in an environment and adapt their responses to that environment, then it would seem that we have captured all those features of human beings that we take into account when we hold them responsible." Deborah G. Johnson discusses another concern: ownership of computer programs. In "Should Computer Programs Be Owned?," Ms. Johnson criticizes utilitarian arguments for ownership, as well as arguments based upon Locke's labor theory of property. The proper limits to extant legal protections, including copyrights, patents, and trade secrecy laws, are called into question. Other emerging concerns include the need to educate the public on the dangers and abuses of computers, and the role of computers in education. To this end, Philip A. Pecorino and Walter Maner present a proposal for a college level course in Computer Ethics, and Marvin J. Croy addresses the ethics of computer-assisted instruction. Dan Lloyd, in his provocative but highly speculative article, "Frankenstein's Children," envisions a world where cognitive simulation AI succeeds in producing machine consciousness, resulting in a possible ethical clash of the rights of artificial minds with human values. The introductory article, James H. Moor's "What is Computer Ethics," is an ambitious attempt to define Computer Ethics, and to explain its importance. According to Moor, the development and proliferation of computers can rightly be termed "revolutionary": "The revolutionary feature of computers is their logical malleability. Logical malleability assures the enormous application of computer technology." Moor goes on to assert that the Computer Revolution, like the Industrial Revolution, will transform "many of our human activities and social institutions," and will "leave us with policy and conceptual vacuums about how to use computer technology." An important danger inherent in computers is what Moor calls "the invisibility factor." In his own words: "One may be quite knowledgeable about the inputs and outputs of a computer and only dimly aware of the internal processing." These hidden internal operations can be intentionally employed for unethical purposes; what Moor calls "Invisible abuse," or can contain "Invisible programming values": value judgments of the programmer that reside, insidious and unseen, in the program. Finally, in the appendix, "Artificial Intelligence, Biology, and Intentional States," editor Terrell Ward Bynum argues against the concept that "intentional states" (i.e. belief, desire, expectation) are causally dependent upon biochemistry, and thus cannot exist within a machine. If you're at all like me, you probably find reading philosophy can be "tough going," and METAPHILOSOPHY is no exception. References to unfamiliar works, and the use of unfamiliar terms occasionally necessitated my reading passages several times before extracting any meaning from them. The topics, however, are quite relevant and their treatment is, for the most part, lively and interesting. With its well-written introductory article, diverse survey of current concerns, and fairly extensive bibliography, this issue of METAPHILOSOPHY is an excellent first source for those new to the field of Computer Ethics. [METAPHILOSOPHY, c/o Expediters of the Printed Word Ltd., 515 Madison Avenue, Suite 1217, New York, NY 10022] Bruce A. Sesnovich mcnc!rti-sel!dg_rtp!sesnovich Data General Corp. rti-sel!dg_rtp!sesnovich%mcnc@csnet-relay.arpa Westboro, MA "Problems worthy of attack prove their worth by hitting back" ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 5 06:53:22 1986 Date: Thu, 5 Jun 86 06:53:20 edt From: vtcs1::in%<> (bundy%aiva.edinburgh.ac.uk@CS.UCL.AC.UK) To: "\\"@cs.ucl.ac.uk Subject: IJCAI AWARDS Status: RO CALL FOR NOMINATIONS FOR IJCAI AWARDS The IJCAI Award for Research Excellence The IJCAI Award for Research Excellence is given at each International Joint Conference on Artificial Intelligence, to a scientist who has carried out a program of research of consistently high quality yielding several substantial results. If the research program has been carried out col- laboratively the award may be made jointly to the research team. The first recipient of this award was John McCarthy in 1985. The Award carries with it a certificate and the sum of $1,000 plus travel and living expenses for the IJCAI. The researcher(s) will be invited to deliver an address on the nature and significance of the results achieved and write a paper for the conference prodeedings. Primarily, however, the award carries the honour of having one's work selected by one's peers as an exemplar of sustained research in the maturing science of Artificial Intelligence. We hereby call for nominations for The IJCAI Award for Research Excellence to be made at IJCAI-87 in Milan. The accompanying note on Selection Procedures for IJCAI Awards provides the relevant details. The Computers and Thought Award The Computers and Thought Lecture is given at each International Joint Conference on Artificial Intelligence by an outstanding young scientist in the field of artificial intelligence. The Award carries with it a certificate and the sum of $1,000 plus travel and subsistence expenses for the IJCAI. The Lecture is one evening during the Conferen- ce, and the public is invited to attend. The Lecturer is in- vited to publish the Lecture in the conference proceedings. The Lectureship was established with royalties received from the book Computers and Thought, edited by Feigenbaum and Feldman; it is currently supported by income from IJCAI funds. Past recipients of this honour have been Terry Winograd (1971), Patrick Winston (1973), Chuck Rieger (1975), Douglas Lenat (1977), David Marr (1979), Gerald Sussman (1981), Tom Mitchell (1983) and Hector Levesque (1985). Nominations are invited for The Computers and Thought Award to be made at IJCAI-87 in Milan. The note on Selection Procedures for IJCAI Awards covers the nomination procedures to be followed. Selection Procedures for IJCAI Awards Nominations for The Computers and Thought Award and The IJCAI Award for Research Excellence are invited from all in the Artificial Intelligence international community. The procedures are the same for both awards. There should be a nominator and a seconder, at least one of whom should not have been in the same institution as the nominee. The nominee must agree to be nominated. There are no other restrictions on nominees, nominators or second- ers. The nominators should prepare a short submission less than 2,000 words for the voters, outlining the nominee's qualifications with respect to the criteria for the parti- cular award. The award selection committee is the union of the Pro- gram, Conference and Advisory Committees of the upcoming IJCAI and the Board of Trustees of IJCAII, with nominees excluded. Nominations should be submitted before December 1st, 1986 to the Conference Chair for IJCAI-87: Dr Alan Bundy, IJCAI-87 Conference Chair, Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, Edinburgh, EH1 IHN, Scotland. tel 44-31-225-7774 ext 242 ArpaNet: bundy@rutgers.arpa JANet: bundy@uk.ac.edinburgh From vtcs1::in%<> Thu Jun 5 06:53:36 1986 Date: Thu, 5 Jun 86 06:53:33 edt From: vtcs1::in%<> (walker@MOUTON.ARPA) To: ailist@sri-ai.arpa, ajcl@ibm.com, arpanet-bboards@mc.lcs.mit.edu Subject: CALL FOR PAPERS for IJCAI-87 Status: RO CALL FOR PAPERS: IJCAI-87 Tenth International Joint Conference on Artificial Intelligence August 23-28, 1987 Milan, Italy The IJCAI conferences are the main forums for the presentation of artificial intelligence research to an international audience. The goal of IJCAI-87 is to promote scientific interchange, within and between all subfields of AI, among researchers from all over the world. The conference is sponsored by the International Joint Conferences on Artificial Intelligence, Inc. (IJCAII). In response to the growing interest in engineering issues within the AI community, IJCAI-87's Technical Program will have two distinct tracks: science and engineering. The science papers, presented Sunday through Wednesday (August 23-26), will stress the computational principles underlying cognition and perception in man and machine. The engineering papers, presented Tuesday through Friday (August 25-28), will highlight pragmatic issues that arise in applying these computational principles. Tutorials will be presented on Sunday and Monday in parallel with the first two days of the science paper presentations. Meetings or workshops focussed on specific research issues might most appropriately be held on Thursday or Friday. TOPICS OF INTEREST Authors are invited to submit papers to either the science or engineering tracks within one of the following topic areas: - Architectures and Languages (including logic programming, user interface technology) - Reasoning (including theorem proving, planning, explaining) - Knowledge Acquisition and Learning (including knowledge-base maintenance) - Knowledge Representation (including task domain analysis) - Cognitive Modeling - Natural Language Understanding - Perception and Signal Understanding (including speech, vision, data interpretation) - Robotics REQUIREMENTS FOR SUBMISSION: Authors are requested to prepare full papers, no more than 7 proceedings' pages (approximately 5600 words), or short papers, no more than 3 proceedings' pages (approximately 2400 words). The full-paper classification is intended for well-developed ideas, with significant demonstration of validity, while the short-paper classification is intended for descriptions of research in progress. Authors must ensure that their papers describe original contributions to or novel applications of AI, regardless of length classification, and that the research is properly compared and contrasted with relevant literature. DETAILS OF SUBMISSION: Authors should submit six (6) copies of their papers (hard copy only -- we cannot accept on-line files) to the Program Chair no later than Monday, January 5, 1987. The following information must be included on the title page: - Author's name, address, telephone number and computer mail address (if applicable) - Paper type (full-paper or short-paper), topic area, track (science or engineering), and a few keywords for further classification within the topic area - An abstract of 100-200 words The timetable is as follows: - Submission deadline: 5 January 1987 (papers received after January 5 will be returned unopened) - Notification of acceptance or rejection: 17 March 1987 - Camera ready copy due: 10 April 1987 The language of the conference is English; all papers submitted should be written in English. REVIEW CRITERIA: Each paper will be reviewed by at least two experts. Acceptance will be based on the overall merit and significance of the reported research, as well as on the quality of the presentation. A paper may be reviewed by experts responsible for an area or track other than the one to which it was submitted if, in the opinion of a program committee member, it can thereby be more fairly reviewed. Papers submitted to the science track should make an original and significant contribution to knowledge in the field of artificial intelligence. Papers submitted to the engineering track should focus on pragmatic issues that arise in reducing AI principles and techniques to practice. Such papers could identify the critical features of some successful application system's approach to reasoning or knowledge acquisition or natural language understanding. Of particular interest are papers that demonstrate insightful analysis of a task domain motivating the selection of a computational and representational approach. CONTACT POINTS: Submissions and inquiries about the program should be sent to the Program Chair: John McDermott Department of Computer Science Carnegie-Mellon University Pittsburgh, PA 15213 USA 1-412-268-2599 McDermott@cmu-cs-a.arpa Inquiries about registration, tutorials, exhibits, and other local arrangements should be sent to the Local Arrangements Chair: Marco Somalvico Dipartimento di Elettronica Politecnico di Milano Piazza Leonardo Da Vinci N.32 I-20133 Milano ITALY 39-2-236-7241 somalvic!prlb2@seismo Other inquiries should be directed to the General Chair: Alan Bundy Department of Artificial Intelligence University of Edinburgh 80 South Bridge Edinburgh EH1 1HN UK 44-31-225-7774 ext 242 Bundy%edinburgh.ac.uk@ucl-cs.arpa From vtcs1::in%<> Fri Jun 6 18:46:35 1986 Date: Fri, 6 Jun 86 18:46:30 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #143 Status: RO AIList Digest Friday, 6 Jun 1986 Volume 4 : Issue 143 Today's Topics: Queries - Medical Expert Systems & MRS & IJCAI Awards Nominations, Opinion - Sexism and Repression, Seminar - Deductive Synthesis of Sorting Programs (SRI), Conference - 1986 SGAICO Conference on 2nd-Generation Expert Systems ---------------------------------------------------------------------- Date: 5 Jun 86 02:23:00 GMT From: hplabs!hplabsb!marvit@ucbvax.berkeley.edu (Peter Marvit) Subject: Medical Expert System availability? (+ Mac query) I ask for a friend who is finishing med school and is looking to "dabble" and/or explore the possiblities... What is a good source of information about medically oriented Expert systems/diagnostics aids? Are PUFF, MYCIN, EMYCIN, and the rest of the famous ones public domain? Are they distributed by commercial folks, if at all? Do you think that such Expert Systems [gawd, I hate the term] will be available in the future on MacIntosh or PC level delivery systems? Finally, I've seen the list of expert system tools for PC. Any personal or anectodatal experiences with them (especially for those who are more domain oriented than AI hackers)? Would someone like to start a similar list of MacIntosh tools? ADVthanksANCE, Peter Marvit ARPA: marvit@hplabs.arpa (no new style, yet) HP LABS UUCP: ...!hplabs!arpa ------------------------------ Date: 4 Jun 86 03:24:24 GMT From: pur-ee!mendozag@ucbvax (Grado) Subject: MRS search I have missed the several discussions about MRS in net.ai, especially related to obtaining sources and documentation. Can anyone provide me with pointers as to how to obtain the sources along with appropriate references ? I would appreciate any help. Victor M Grado Box 62, School of Electrical Engineering, Purdue University West Lafayette, IN 47907 (317) 494-3494 ARPA: mendozag@ee.purdue.edu [I will send copies of the previous discussion (AIList V. 4, Nos. 11, 15, 17, 21, 32). -- KIL] ------------------------------ Date: 4 Jun 86 17:40:12 GMT From: cad!nike!sri-spam!klee@ucbvax.berkeley.edu (Ken Lee) Subject: Re: MRS search Contact Professor Mike Genesereth, Computer Science Dept., Stanford Univeristy, Stanford, CA 94305 (genesereth@su-sushi.arpa) for information. I think he's in charge of the MRS team. Also, if anyone saved the MRS discussion, could you send me a copy, please. I'm new to the net and did not get it. I just finished Prof. Genesereth's expert systems course, using MRS, and I'm interested other people's opinions and comments on MRS. Thanks much. Ken Lee arpanet: klee@sri-spam uucp: ucbvax!klee\@sri-spam.arpa ------------------------------ Date: 5 Jun 86 20:03:08 GMT From: CS.UCL.AC.UK!bundy%aiva.edinburgh.ac.uk@ucbvax.berkeley.edu (Alan Bundy) Subject: IJCAI Awards Nominations CALL FOR NOMINATIONS FOR IJCAI AWARDS The IJCAI Award for Research Excellence The IJCAI Award for Research Excellence is given at each International Joint Conference on Artificial Intelligence, to a scientist who has carried out a program of research of consistently high quality yielding several substantial results. If the research program has been carried out col- laboratively the award may be made jointly to the research team. The first recipient of this award was John McCarthy in 1985. The Award carries with it a certificate and the sum of $1,000 plus travel and living expenses for the IJCAI. The researcher(s) will be invited to deliver an address on the nature and significance of the results achieved and write a paper for the conference prodeedings. Primarily, however, the award carries the honour of having one's work selected by one's peers as an exemplar of sustained research in the maturing science of Artificial Intelligence. We hereby call for nominations for The IJCAI Award for Research Excellence to be made at IJCAI-87 in Milan. The accompanying note on Selection Procedures for IJCAI Awards provides the relevant details. The Computers and Thought Award The Computers and Thought Lecture is given at each International Joint Conference on Artificial Intelligence by an outstanding young scientist in the field of artificial intelligence. The Award carries with it a certificate and the sum of $1,000 plus travel and subsistence expenses for the IJCAI. The Lecture is one evening during the Conferen- ce, and the public is invited to attend. The Lecturer is in- vited to publish the Lecture in the conference proceedings. The Lectureship was established with royalties received from the book Computers and Thought, edited by Feigenbaum and Feldman; it is currently supported by income from IJCAI funds. Past recipients of this honour have been Terry Winograd (1971), Patrick Winston (1973), Chuck Rieger (1975), Douglas Lenat (1977), David Marr (1979), Gerald Sussman (1981), Tom Mitchell (1983) and Hector Levesque (1985). Nominations are invited for The Computers and Thought Award to be made at IJCAI-87 in Milan. The note on Selection Procedures for IJCAI Awards covers the nomination procedures to be followed. Selection Procedures for IJCAI Awards Nominations for The Computers and Thought Award and The IJCAI Award for Research Excellence are invited from all in the Artificial Intelligence international community. The procedures are the same for both awards. There should be a nominator and a seconder, at least one of whom should not have been in the same institution as the nominee. The nominee must agree to be nominated. There are no other restrictions on nominees, nominators or second- ers. The nominators should prepare a short submission less than 2,000 words for the voters, outlining the nominee's qualifications with respect to the criteria for the parti- cular award. The award selection committee is the union of the Pro- gram, Conference and Advisory Committees of the upcoming IJCAI and the Board of Trustees of IJCAII, with nominees excluded. Nominations should be submitted before December 1st, 1986 to the Conference Chair for IJCAI-87: Dr Alan Bundy, IJCAI-87 Conference Chair, Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, Edinburgh, EH1 IHN, Scotland. tel 44-31-225-7774 ext 242 ArpaNet: bundy@rutgers.arpa JANet: bundy@uk.ac.edinburgh ------------------------------ Date: Mon 2 Jun 86 23:03:05-PDT From: Lee Altenberg Subject: Re: Backward AI May I take this opportunity to be a "righty" and attempt to reprogram the software of Tom Tedrick by expressing my dismay with his sexist description of women as inexplicably trying to "poison" the efficiency of their husbands CPU's. One should be careful about attributing to whole classes of people the traits of one's personal friends. Also, the milk request was interpreted as being a passive-aggressive act. This represents repressed anger which should be brought to the surface. ------------------------------ Date: Thu 5 Jun 86 15:25:33-PDT From: Amy Lansky Subject: Seminar - Deductive Synthesis of Sorting Programs (SRI) DEDUCTIVE SYNTHESIS OF SORTING PROGRAMS Jon Traugott (JCT@SAIL) Stanford University 11:00 AM, MONDAY, June 9 SRI International, Building E, Room EJ228 (new conference room) Using the deductive synthesis framework developed by Manna and Waldinger we have derived a wide variety of recursive sorting programs. These derivations represent the first application of the deductive framework to the derivation of nontrivial algorithms. While the programs given were derived manually, we ultimately hope that a computer implementation of the system (of which none currently exists) will find similar programs automatically. Our derivations are intended to suggest this possibility; the proofs are short in relation to program complexity (on the order of 20 steps per procedure) and individual derivation steps are uncontrived. We also present a new rule for the generation of auxiliary procedures, a common "eureka" step in program construction. VISITORS: Please arrive 5 minutes early so that you can be escorted up from the E-building receptionist's desk. Thanks! ------------------------------ Date: 5 JUN 86 18:10-N From: SCHNEIDER%CGEUGE51.BITNET@WISCVM.WISC.EDU Subject: Conference - 1986 SGAICO Conference on 2nd-Generation Expert Systems SGAICO (swiss group for artificial intelligence and cognitive science) 1986 SGAICO CONFERENCE ON SECOND GENERATION EXPERT SYSTEMS (including SGAICO General Assembly) Luc Steels, Walter Van de Velde University of Brussels with exhibition Holiday-Inn, Zurich-Regensdorf Wednesday, October 22 1986 PURPOSE SGAICO is organizing a conference on 2nd generation expert systems. The purpose of the conference is to inform participants in depth about this important new trend in expert system technology. First generation expert systems - which are normally based on associative if-then rules - are subject to severe limitations. These include reasoning power in general, explanations, natural language capabilities, ungraceful degradation and learning capacity. One of the reasons for these limitations is a lack of causal knowledge about the problem domain. Expert systems of the second generation include models of the underlying causal dependencies that are used in non-trivial reasoning processes. Professor Luc Steels and his group are among the leading researchers on Second Generation Expert Systems. Luc Steels will give the general keynote speech. His collaborator van de Velde will discuss a second generation expert system in depth. A demonstration will be presented on a Lisp machine. PARTICIPANTS This conference is intended for computer-scientists, engineers, managers and all those wishing to keep up with the latest developments in this fast-moving field. We expect participants to have some minimal previous knowledge of expert systems. SGAICO GENERAL ASSEMBLY The SGAICO general assembly (11:00-12:30) includes a discussion of long-term development of AI in Switzerland. We are pleased to link our meeting to a Gottlieb Duttweiler Institute (GDI) event: USER INTERFACES - GATEWAY OR BOTTLENECK New Trends of Access to Information and Knowledge October 20-21, 1986 This 4th International Symposium for Advanced Information Technology presents new solutions to the problem of interaction between users and computers in management and industry. Key topics are: End User Systems, Mangement Support Systems, Natural Language Understanding, Decision Support Systems, Intelligent Query Systems, Process Control, CAD, Maintenance/Diagnosis, Simulation. PROGRAM Speakers Luc Steels, Walter Van de Velde, Artificial Intelligence Laboratory, Vrije Universiteit, Brussels 9:00 - 10:30 Keynote talk by Luc Steels: Emerging trends in expert systems 11:00 - 12:30 SGAICO General Assembly: Long-term development of AI in Switzerland. Moderator: Guenter Albers 14:00 - 15:30 Walter Van de Velde: Learning and deep reasoning in second generation expert systems (part I) 16:00 - 17:30 Walter Van de Velde (part II) 17:45 - 19:00 Demonstrations on Lisp-Machines 19:00 Informal "get-together" exhibition including major Artificial Intelligence software and hardware. ORGANIZATION Program Committee Guenter Albers, University of Geneva Rolf Pfeifer, University of Zurich Michael Rosner, University of Geneva Daniel Schneider, University of Geneva (Chairman) Patrick Shann, University of Geneva Fees SI members or members of a SVI/FSI organisation 110.- Sfr non members 180.- Sfr student rates 30.- Sfr Special rates Limited funding is available for persons with financial needs who wish to apply for student rates. Registration Please fill out the registration card and mail it by september 30 1986. You will be billed when receiving confirmation. Telephone of the SI/SGAICO secretariat: (..41) 1 481 73 90 (Frau Nicolet) Lunch Please indicate on the registration form if you plan to have lunch at the Holiday Inn. Accomodation For hotel registration please contact the Tourist Office, Bahnhofplatz 15, 8023 Zurich, Tel.: (..41) 1 211 40 00, or the Holiday Inn, Regensdorf, Tel.: (..41) 1 840 25 20. For further information about the program contact a program committee member or email to Daniel Schneider (sender). For information on the GDI congress, please contact: Gottlieb Duttweiler Institut Frau Kunz-Wechler CH-8803 Ruschlikon Tel.: (01) 461 37 16 To register contact: SI/SGAICO Postfach 570 CH-8027 Zurich Switzerland from: Daniel K.Schneider Departement de Science Politique, Universite de Geneve 1211 GENEVE 4 (Switzerland), Tel. (..41) 22 20 93 33 ext. 2357 to VMS/BITNET: to UNIX/EAN: BITNET: SCHNEIDER@CGEUGE51 shneider%cui.unige.chunet@CERNVAX ARPA: SCHNEIDER%CGEUGE51.BITNET@WISCVM shneider%cui.unige.chunet@ubc.csnet uucp: mcvax!cernvax!cui!shneider X.400/ean: shneider@cui.unige.chunet ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 10 06:52:51 1986 Date: Tue, 10 Jun 86 06:52:40 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #144 Status: RO AIList Digest Tuesday, 10 Jun 1986 Volume 4 : Issue 144 Today's Topics: Literature - Report Sources & Bibliography #1 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Report Sources Mrs. A. McCauley Department of Computer Science University of Manchester Oxford Road Manchester, M13 9PL England Payment should be made by sterling cheque made payable to the University of Manchester Technical Reports Librarian Computer Science Department University of Wisconsin 1210 W. Dayton St. Madison, WI 53706 F. Renzetti IMAG B.P. 68 38402 St MARTIN D'HERES (France) Technical Reports Secretary Department of Computer Science University of Melbourne Parkville, Victoria, 3052 AUSTRALIA (Donations of $5.00 per tech report requested) Naomi Schulman Publications Computer Systems Laboratory Stanford University Stanford, CA 94305 Centre for Mathematics and Computer Science Postbus 4079 1009 AB Amsterdam The Netherlands (Foreign payments are subject to a surcharge to cover bank, postal and handling charges) Ms. K. M. Garcia Technical Librarian Department of Computer Science University of California, Santa Barbara Santa Barbara, CA 93106 Computing Research Laboratory University of Michigan Room 1079, East Engineering Building Ann ARbor, Michigan 48109 L. A. Stratmann Department of Computer Science Rice University P. O. Box 1892 Houston, Texas 77251 Department of Computer Sciences Technical Report Center The University of Texas at Austin Austin, Texas CS.TECH@UTEXAS-20 Virginia Polytechnic Institute and State University Department of Computer Science 562 McBryde Hall Blacksburg, VA 24061 ------------------------------ Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Bibliography #1 %A William R. Arnold %A John S. Bowie %T Artificial Intelligence: A Personal Commonsense Journey %I Prentice Hall %D 1986 %K AT15 %X 24.95, ISBN 0-13-148877-1 219 pages %A Luc Steels %A John A. Campbell %T Progress in Artificial Intelligence %D 1985 %K AT15 %A Rodney A. Brooks %T Programming in Common Lisp %I John Wiley and Sons %D 1985 %K AT15 T01 %X ISBN 0-471-818888-7 %A Ajit Narayanan %A Noel E. Sharkey %T An Introduction to Lisp %I Chichester: Ellis Horwood %D 1985 %K AT15 T01 %X ISBN 0-470-20244-0 paperback %A Alain Bonet %T Artificial Intelligence: Promise and Performance %I Prentice-Hall %D 1985 %K AT15 %X 221 pages ISBN 0-13-048869-0 %A Wendy B. Rauch-Hindin %T Artificial Intelligence in Business, Science and Industry, Volume I: Fundamentals %I Prentice-Hall %D 1985 %X 331 pages ISBN-0-134-048893-3 $34.95 %A Wendy B. Rauch-Hindin %T Artificial Intelligence in Business, Science and Industry, Volume II: Applications %I Prentice-Hall %D 1986 %X 348 pages ISBN-0-134-048901-3 $34.95 %A Tim Johnson %T Natural Language Computing: The Commercial Applications %I Ovum Limited %C London %K AI02 AT04 %A B. K. Boguraev %A K. S. Jones %T A Framework for Inference in Natural Language Front Ends to Databases %I University of Cambridge Computer Laboratory %R Report No. 64 %D 1985 %K AI02 AA09 %A F. J. Damerau %T An Interactive Customization Program for a Natural Language Database Query System %I IBM Research Division %R Report No. 10411 %D 1984 %K AI02 AA09 %A F. J. Damerau %T Problems and Some Solutions in Customization of Natural Language Data Base Front Ends %I IBM Research Divison %D 1984 %R Report No. 10872 %K AI02 AA09 %A H. Enomoto %T TELL: a Natural Language Based Software Development System %I Institute for New Generation Computer Technology %D 1984 %R Report No. 67 %K AI02 %A R. E. Frederking %T Syntax and Semantics in Natural Language Parsers %I Carnegie-Melon University, Department of Computer Science %R Report No. 85-133 %D 1985 %K AI02 %A P. S. Jacobs %T PHRED: A Generator for Natural Language Interfaces %I University of California, Berkeley Computer Science Division %R Report No. 85-198 %D 1985 %K AI02 %A D. E. Johnson %T Design of a Robust, Portable Natural Language Interface Grammar %I IBM Research Division %R Report No. 10867 %D 1984 %K AI02 %A J. K. Kalita %T Generating Summary Responses to Natural Language Database %I University of Saskatchewan %R Report No. 84-9 %D 1984 %K AI02 AA09 %A E. Mays %T A Modal Temporal Logic for Reasoning About Changing Database with Applications to Natural Language Question Answering %I University of Pennsylvania, Moore School of Electrical Engineering. Department of Computer Science %D 1985 %R Report No. 85-01 %K AI02 AI10 AA09 %A B. Neuamnn %T Natural Language Descriptions of Time-Varying Scenes %I Universitaet Hamburg. Fachbereich Informatik %R Report No. 105 %D 1984 %K AI02 AI06 %A E. Orlowska %T The Montague Formalization of Natural Language %I Polish Academy of Sciences, Institute of Computer Sciences %R Report No. 548 %D 1984 %K AI02 %A S. R. Petrick %T Natural Language Database Query Systems %I IBM Research Division %R Report No. 10508 %D 1984 %K AI02 %A P. Saint-Dizier %T An Approach to Natural Language Semantics in Logic Programming %I Institute National de Recherce en Informatique et en Automatique %R Report No. 389 %K AI02 AI10 $A L. F. Rau %T The Understanding and Generation of Ellipses in a Natural Language Systems. %I University of California Berkeley. Computer Science Division %D 1984 %R Report No. 85-227 %K AI02 %T Dynamic Computer Simulation of Multiple Closed-Chain Robotic Mechanisms %A Se-Young Oh %A David E. Orin %B BOOK28 %K AI07 %T On Dynamic Models of Robot Force Control %A Steven D. Eppinger %A Warren P. Seering %B BOOK28 %K AI07 %T Arm Signature Identification %A Henry W. Stone %A Arthur C. Sanderson %A Charles P. Neuman %T The Effects of Dynamic Models on Robot Control %A M B. Leahy Jr %A K. P. Valavanis %A G. N. Saridi %B BOOK28 %K AI07 %T Experimental Determination of the Effect of Feedforward Control on Trajectory Tracking Errors %A Chae H. An %A Christopher G. Atkeson %A John M. Hollerbach %B BOOK28 %K AI07 %T Low Level Control for the Utah/MIT Dextrous Hand %A K. B. Biggers %A S. C. Jacobsen %A G. E. Gerpheide %B BOOK28 %K AI07 %T Hybrid Position/Force Control of Multi-Arm Cooperating Robots %A Sama Hayati %B BOOK28 %K AI07 %T Solving a Two Dimensional Path Planning Problem Using Topographical Knowledge of the Environment and Capability Constraints %A R. F. Richbourg %B BOOK28 %K AI07 %T Implementing a Force Strategy for Object Re-orientation %A Ronald S. Fearing %B BOOK28 %K AI07 %T On-Line Pathfinding in Multi-Robot Systems including Obstacles - %A E. Freund %A H. Hoyer %B BOOK28 %K AI07 %T Video Image Stereo Matching Using Phase-Locked Techniques %A W. Thomas Miller III %B BOOK28 %K AI07 AI06 %T An Approach to 3-D Object Identification Using Range Images %A David B. Shu %A C. C. Li %A Y. N. Sun %B BOOK28 %K AI07 AI06 %T Sensing and Describing 3-D Structure %A Peter K. Allen %B BOOK28 %K AI07 AI06 %T A New Decomposition for Three-Dimensional Contours Based on Curvature and Torsion %A N. Kehtarnavaz %A R. J. P.de Figueiredo %B BOOK28 %K AI07 AI06 %T Soft Configuration in Automated Insertion %A C. B. Lofgren %B BOOK28 %K AI07 AA26 AA04 %T Part Dispatch in Multistage Card Lines %A Ram Akella %B BOOK28 %K AA26 %T Throughput Maximization in Short Cycle Automated Manufacturing %A M. H. Han %B BOOK28 %K AA26 %T Job Scheduling Model for a Flexible Manufacturing Machine %A C. S. Tang %B BOOK28 %K AA26 %T Graphical Simulation and Automatic Verification of NC Maching Programs %A U. Sungurtekin %A H. B. Voecker %B BOOK28 %K AA26 %T Real-time Verification of Multi-Axis NC Machining Programs with Raster Graphics %A W. P. Wang %A K. K. Wang %B BOOK28 %K AA26 %T Real-time Error Compensation System for A Computerized Numerical Control Turning Center %A Alkan Donmez %A Kang Lee %A C. Richard Liu %A Moshe M. Barash %B BOOK28 %K AA26 %T Adaptive Control of Robot Manipulators - A Review %A T. C. Hsia %B BOOK28 %K AI07 %T Automatic Generation of the Dynamic Equations of the Robot Manipulators using a Lisp Program %A Albert Izaguirre %A Richard Paul %B BOOK28 %K AI07 T01 %A M. A. Peskin %A A. C. Sanderson %T Manipulation of a Sliding Object %B BOOK28 %K AI07 %A Rajko Tomovic %A George A. Bekey %T Robot Control by Reflex Actions %B BOOK28 %K AI07 %A M. Togai %A O. Yamano %T Learning Control and its Optimality: Analysis and its Applications to Controlling Industrial Robots %B BOOK28 %K AI07 AI04 %A Ataru Nakamura %A Kang G. Shin %A Neil D. McKay %T Automatic Generation of Trajectory Planners for Industrial Robots %B BOOK28 %K AI07 %A G. N. Saridis %A K. P. Valavahnis %T Mathematical Formulation of the Organization Level of an Intelligent Machine %B BOOK28 %K AI07 %A Morikazu Takegaki %A Tadashi Ohi %T An Advanced Design Support System for Intelligent Robots %B BOOK28 %K AI07 %A Ricard Cassinis %T Automatic Resource Allocation in Industrial Multirobot Systems %B BOOK28 %K AI07 %A Michael J. Swain %A Joseph L. Mundy %T Experiments in Using a Theorem Prover to Prove and Develop Geometrical Theorems in Computer Vision %B BOOK28 %K AI06 AI11 AA13 AI14 %A W. Eric L. Grimson %T Disambiguating Sensory Interpretations Using Minimal Sets of Sensory Data %B BOOK28 %K AI06 %A H. S Yang %A A. C. Kak %T Determination of the Identity, Position and Orientation of the Topmost Object in a Pile %B BOOK28 %K AI06 %A Judith F. Silverman %A David B. Cooper %T Unsupervised Estimation of Polynomial Approximations to Smooth Surfaces in Images or Range Data %B BOOK28 %K AI06 %A P. J. Englert %A P. K. Wright %T Applications of Artificial Intelligence in the Design of Fixtures for Automated Manufacturing %B BOOK28 %K AA26 %A Patrick Fitzhorn %A Wade O. Troxell %T A Dynamic Approach to the Robotic Design Cycle %B BOOK28 %K AI07 %A M. Dado %A A. H. Soni %T A Generalized Approach for Forward and Inverse Dynamics of Elastic Manipulators %B BOOK28 %K AI07 %A R. Marino %A S. Nicosia %A A. Tornambe %T Dynamic Modelling of Flexible Robot Manipulators %B BOOK28 %K AI07 %A Gregory P. Starr %T Edge Following with a PUMA 560 Manipulator Using VAL-II %B BOOK28 %K AI07 %A M. Silva %A L. Montano %A P. Pardos %T Terminal Controllers for Robots: Shooting and Optimal Control %B BOOK28 %K AI07 %A Christopher Clark %A Lawrence Stark %T Cooperative Robot Control %B BOOK28 %K AI07 %A Gerhard Hirzing %A J. Dietrich %T Multisensory Robots and Sensorbased Path Generators %B BOOK28 %K AI07 AI06 %A E. G. Harokops %T Optimal Learning Control of Mechanical Manipulators in Repetitive Motions %B BOOK28 %K AI07 AI04 %A John Wen %A Alan Desrochers %T Sub-Time-Optimal Control Strategies for Robotic Manipulators %B BOOK28 %K AI07 %A M. B. Leahy %A George N. Saridis %T The RAL Hierarchical Control System %B BOOK28 %K AI07 %A Kang G. Shin %A Neil D. McKay %T Minimum Time Trajectory Planning for Industrial Robots with General Torque Constraints %B BOOK28 %K AI07 %A H. Kazerooni %A P. E. K. Houpt %A T. B. Sheridan %T Robust Compliant Motion for Manipulators, Part I: The Fundamental Concept of Compliant Motion; Part II: Design Methods %B BOOK28 %K AI07 %A Mary M. Moya %A William M. Davidson %T Sensor Driven Factor Tolerant Control of a Maintenance Robot %B BOOK28 %K AI07 %A Richard J. Grommes %A Michael P. Hennessey %A Warren J. Dick %T Adaptive Intervehicle Positioning for Robotic Material Transfer %B BOOK28 %K AI07 %A S. Thunborg %T A Remote Maintenance Robot System for a Pulsed Nuclear Reactor %B BOOK28 %K AI07 %A Nobuyoshi Yokobori %A Pen-shu Yeh %A Azriel Rosenfield %T Sub-Pixel Geometric Correction of Pictures by Calibration and Decalibration %B BOOK28 %K AI06 %A Ichiro Masaki %T Modular Multi-Resolution Vision Processor %B BOOK28 %K AI06 %A Ronald Lumia %T Rapid Hidden Feature Elimination Using an Octree %B BOOK28 %K AI06 %A Nien-hu Chao %A E. N. Schiebel %T Inspection Assistant - A Knowledge-Based System for Piece Part Inspection %B BOOK28 %K AI06 %A Agostino Pl. M. Villa %A Roberto Mosca %A Giuseppe Murari %T Expert Control Theory: A Key for Solving Production Planning Control Problem in Flexible Manufacturing %B BOOK28 %K AA26 %A R. Ippolito %A S. Rosseto %A M. Vallauri %A A. P. M. Villa %T The Emergence of Artificial Intelligence Applications in Manufacturing %B BOOK28 %K AA26 %A Caludio Boer %T Expert Control System Requirements for Manufacturing Process Control %B BOOK28 %K AA26 %A Cynthia K. Whitney %T Building "Expert Systems" When No Experts Exist %B BOOK28 %K AA26 AI01 %A Alan A. Desrochers %A Christopher M. Seaman %T A Projection Method for Simplifying Robot Manipulator Models %B BOOK28 %K AI07 %A Brian Armstrong %A Oussama Khatib %A Joel Burdick %T The Explicit Dynamic Model and Intertial Parameters of the PUMA 560 ARM %B BOOK28 %K AI07 %A M. B. Leahy Jr., %A L. M. Nugent %A K. P. Valavanis %A G. N. Saridis %T Efficient Dynamics for a PUMA 600 %B BOOK28 %K AI07 %A R. B. Kelley %T Vertical Integration for Robot Assembly Cells %B BOOK28 %K AI07 %A S. A. Cameron %A R. K. Culley %T Determining the Minimum Translational Distance Between Two Convex Polyhedra %B BOOK28 %K AI07 O06 %A Walter Meyer %T Distance Between Boxes: Applications to Collision Detection and Clipping %B BOOK28 %K AI07 %A R. Alami %A H. Chochon %T NNS, a Knowledge-Based On-Line System for an Assembly WorkCell %B BOOK28 %K AI07 %A A. Rovetta %A G. Frosi %T Logical Structure for Assembly with Robot %B BOOK28 %K AI07 %A J. R. Stenstrom %A C. I. Connolly %T Building Wire Frames from Multiple Range Views %B BOOK28 %K AI07 AI06 %A X. Zhuang %A T. S. Huang %T From Two-View Motion Equations to Three-Dimensional Motion Parameters and Surface Structure: A Direct and Stable Algorithm %B BOOK28 %K AI07 %A Giulio Sanino %A Massimo Tistarelli %T Analysis of Object Motion and Camera Motion in Real Scenes %B BOOK28 %K AI06 %A J. Amat %A A. Casals %A V. Llario %T Improving Accuracy and Resolution of a Motion Stereo Vision System %B BOOK28 %K AI06 %A B. Chernuschi-Frias %A D. B. Cooper %A P. N. Belhumeur %T 3-D Object Position Estimation and Recognitions Based on Parameterized Surfaces and Multiple Views %B BOOK28 %K AI06 %A G. M. Acaccia %A R. C. Michelini %A R. M. Molfiono %A P. A. Piaggio %T X-SIFIP: A Knowledge-based Special Purpose Simulator for the Development of Flexible Manufacturing Cells %B BOOK28 %K AA26 %A Andrew Kusiak %T FMS Scheduling: A Crucial Tool in an Expert Control Structure for Production Planning %B BOOK28 %K AA26 AI01 %A Jon D. Erickson %A Aaron Cohen %T Autonomous Robotic Aspects of the Space Station Program %B BOOK28 %K AI07 AA27 %A W. Kohn %A K. Healy %T On-Line Task Interpreter for Astrobot %B BOOK28 %K AI07 AA27 %A Scott Y. Harmon %A Douglas W. Grange %A Walter A. Aviler %T Techniques for Coordinating Autonomous Robots %B BOOK28 %K AI07 %A Mark A. Bronez %A Margaret M. Clarke %A Alberta Quinn %T Requirements Development for a Free-Flying Robot -- The Robin %B BOOK28 %K AI07 AA19 %A Jeffrey S. Schoenwald %A Michael S. Balck %A Gregory A. Arnold %A Timonthy A. Allison %T Improved Robot Trajectory from Acoustic Range Servo Control %B BOOK28 %K AI07 %A Ljubomir T. Grujic %T Tracking Analysis for Non-Stationary Non-Linar Discrete-Time System %B BOOK28 %K AI07 %A Tomoaki Kubo %A George Anwar %A Masayoshi Tomizuka %T Applications of Nonlinear Friction Compensation to Robot Arm Control %B BOOK28 %K AI07 %A Daniel E. Whitney %T Real Robots Don't Need Jigs %B BOOK28 %K AI07 AA26 %A Margo K. Apostolos %T Robot Choreography: An Aesthetic Application in User Acceptance of a Robot Arm %B BOOK28 %K AI07 AA25 O01 %A Stuart G. Stanley %A Mansour Eslami %T On Design of an Educational Robot %B BOOK28 %K AI07 AT18 %A P. J. Becker %T Sensor Information Processing in Robot Control Systems %B BOOK28 %K AI07 %A Gerard Medioni %A Yoshio Yasumoto %T Corner Detection and Curve Representation Using Cubic B-Splines %B BOOK28 %K AI06 %A Xueyin Lin %A William G. Lee %T SDFS: A New Strategy for the Recognition of Object Using Range Data %B BOOK28 %K AI06 %A Bir Bhanu %A John C. Ming %T Recognition of 2-D Occluded Objects using a Cluster-Structure Paradigm %B BOOK28 %K AI06 %A Michael Magee Mitchell Nathan %T A Theorem Proving Based Pattern Recognition System %B BOOK28 %K AI06 AI11 AI14 %A Patricia McConail %T Automation and CIMS in the Esprit Program %B BOOK28 %K AA26 %A Ulrich Rembold %A M. Vojnovic %T Operational Control for Robot Systems Integration into CIM %B BOOK28 %K AA26 AI07 %A Lyle M. Jenkins %T Telerobotic Work System- Space Robotics Application %B BOOK28 %K AI07 AA27 %A David L. Akin %T Parametric Testing of Space Teleoperators through Neutral Buoyancy Simulation %B BOOK28 %K AI07 AA27 %A T. Sheridan %T Human Supervisory Control of Robot System %B BOOK28 %K AI07 O01 %A Jack Pennington %T (I) Space Telerobotics: A Few More Hurdles %B BOOK28 %K AI07 AA27 %A Fredrik Dessen %T Coordinating Control of a Two Degrees of Freedom Universal Joint Structure Driven by Three Servos %B BOOK28 %K AI07 %A Chang-huan Liu %A Yen-ming Chen %T Multimicroprocessor-based Cartesian Space Control %B BOOK28 %K AI07 %A Subbiah Mahalingam %A Anand M. Sharan %T The Optimal Balancing of the Robotic Manipulators %B BOOK28 %K AI07 %A N. Sreenath %A P. S. Krishnaprasad %T DYNAMAN: A Tool for Manipulator Design and Analysis %B BOOK28 %K AI07 %A Sanjeev R. Maddila %T Motion Planning Algorithm for a Ladder Among Rectangular Obstacles %B BOOK28 %K AI07 O06 %A Michael Erdmann %A T. Lozano-Perez %T On Multiple Moving Objects %B BOOK28 %K AI07 %A Michael Brady %T Recent Advances Toward a Surface Primal Sketch %B BOOK28 %K AI06 %A Martial Hebert %A Takeo Kanade %T Range Data Analysis of Outdoors Scenes %B BOOK28 %K AI06 %A N. Ayache %A O. D. Faugeras %A B. Faverjon %A F. Lustman %T Building Visual Maps by Combining Noisy Stereo Measurements %B BOOK28 %K AI06 %A T. Poggio %A Michael Drumheller %T Parallel Stereo %B BOOK28 %K AI06 H03 Thinking Machines %A S. Harmon %A G. Bianchini %A B. Pinz %T Sensor Data Fusion Through a Distributed Blackboard %B BOOK28 %K AI06 %A J. Crowley %T Generalized Surface Patches: A Representation for Composite Surface Modeling %B BOOK28 %K AI06 %A K. Jo. Overton %T Range Vision, Force, and Tactile Sensory Integration: Issues and an Approach %B BOOK28 %K AI06 AI07 %A H. Durrant-Whyte %T Integration of Distributed Sensor Observation %B BOOK28 %K AI06 AI07 %A Waj-Joon Lee %A David E. Orin %T The Kinematics of Legged Locomotion Over Uneven Terrain %B BOOK28 %K AI07 %A U. Ozguner %T Control of Quadruped Trot %B BOOK28 %K AI07 %A Chi-Keng Tsai %A David E. Orin %T Using Proximity Sensing in Robot Leg Control %B BOOK28 %K AI07 %A Jagdish Joshi %A Alan A. Desrochers %T Modeling and Control of a Mobile Robot Subject to Disturbances %B BOOK28 %K AI07 %A Hiroaki Kobayashi %T Grasping and Manipulation of Objects by Articulated Hands %B BOOK28 %K AI07 %A Steve Jacobsen %A E. K. Iversen %A D. F. Knutti %A R. T. Johnson %A K. B. Biggers %T Machinery Issues in End Effector Design %B BOOK28 %K AI07 %A Mark R. Cutosky %A Pual K. Wright %T Modeling Manufacturing Grips and Correlations with the Design of Robotic Hands %B BOOK28 %K AI07 AA26 %A J. C. Becker %A N. V. Thakor %A K. G. Gruben %T A Study of Human Hand Tendon Kinematics with Applications to Robot Hand Design %B BOOK28 %K AI07 %A Michael A. Erdman %A Matthew T. Mason %T An Exploration of Sensorless Manipulation %B BOOK28 %K AI07 %A Randy C. Brost %T Automatic Grasp Planning in the Presence of Uncertainty %B BOOK28 %K AI07 O04 AI09 %A Juan Juan %A R. P. Paul %T Model for Automatic Programming of Fine-Motion in Assemblies %B BOOK28 %K AI07 %A Bruce R. Donald %T Robot Motion Planning with Uncertainty in the Geometric Models of the Robot Environment: A Formal Framework for Error Detection and Recovery %B BOOK28 %K AI07 O04 AI09 %A Tsuji %T Recent Advances Toward the Realization of a Flexible Mobile Vehicle %B BOOK28 %K AI07 AA19 %A Allen M. Waxman %A Jacqueline Le Moigne %A Larry S. Davis %A Eli Liang %A Tharakesh Siddalingaiah %T A Visual Navigation Systems %B BOOK28 %K AI07 AI06 %A Y. Y. Huang %A Z. L. Cao %A E. L. Hall %T Region Filling Operation for Mobile Robot Using Computer Graphics %B BOOK28 %K AI07 AA19 %A Richard Wallace %A Kichie Matsuzaki %A Yoshimasa Goto %A Jon Webb %A Jill Crisman %A Takeo Kanade %T Progress in Robot Road Following %B BOOK28 %K AI07 AA19 %A C. Thorpe %A S. Shafer %A A. Stentz %T An Architecture for Data Fusion %B BOOK28 %K AI06 sensors %A M. Shimojo %A O. Khatib %T Intelligent Fusion of Tactile Sensor Data %B BOOK28 %K AI07 AI06 %A D. Morley %A S. Chiu %A J. Martin %T Sensor Data Fusion on a Parallel Processor %B BOOK28 %K AI07 H03 AI06 %A E. W. Kent %A M. Shneier %A T. H. Hong %T Building Representations from Fusions of Multiple Views %B BOOK28 %K AI07 AI06 %A E. Bensana %A M. Correge %A G. Bel %A D. Dubois %T An Expert System Approach to Industrial Job Shop Scheduling %B BOOK28 %K AI07 AA26 AA05 AI01 %A J. Erschler %A P. Esquirol %T Decision Aid in Job Shop Scheduling: A Knowledge Based Approach %B BOOK28 %K AI07 AA26 %A Alexandre M. Parodi %A John J. Nitao %A Louis S. McTamaney %T An Intelligent System for an Autonomous Vehicle %B BOOK28 %K AI07 AA19 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 10 06:53:12 1986 Date: Tue, 10 Jun 86 06:52:55 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #145 Status: RO AIList Digest Tuesday, 10 Jun 1986 Volume 4 : Issue 145 Today's Topics: Literature - Bibliography #2 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Bibliography #2 %A C. S. G. Lee %A P. R. Chang %T Efficient Parallel Algorithm for Robot Inverse Dynamics Computation %B BOOK28 %K AI07 H03 %A Shgaheen Ahmad %T Real-Time Multi-processor Based Robot Control %B BOOK28 %K AI07 %A V. Dupourque %A H. Guiot %A O. Ischacian %T Towards Multi-Processor and Multi-Robot Controllers %B BOOK28 %K AI07 H03 %A John M. Hollerbach %A John E. Wood %T Finger Force Computation without the Grip Jacobian %B BOOK28 %K AI07 %A John Jameson %A Larry Leifer %T Quasi-Static Analysis: A Method for Predicting Grasp Stability %B BOOK28 %K AI07 %A Van-Duc Nguyen %T The Synthesis of Stable Grasps in the Plan %B BOOK28 %K AI07 %A James Barber %A Richard A. Volz %A Rajiv Desai %A Ronitt Rubenfeld %A Brian Schipper %A Jan Wolter %T Automatic Two-Fingered Grip Selection %B BOOK28 %K AI07 %A Dinesh K. Pai %A M. C. Leu %T INEFFABELLE - An Environment for Interactive Computer Graphic Simulations of Robotic Applications %B BOOK28 %K AI07 %A S. A. Hutchinson %A A. C. Kak %T FProlog: A Language to Integrate Logic and Functional Programming for Automated Assembly %B BOOK28 %K AI07 T02 AI10 %A Mitchell S. Steffen %A Timothy J. Greene %T An Application of Hierarchical Planning and Constraint-directed Search to Scheduling Parallel Procesors %B BOOK28 %K AI07 H03 AI09 %A John T. Fedema %A Shaheen Ahmad %T Determining a Static Robot Grasp for Automated Assembly %B BOOK28 %K AI07 %A Thomas F. Knoll %A Ramesh C. Jain %T Recognizing Partially Visible Objects Uising Feature Indexed Hypotheses %B BOOK28 %K AI07 AI06 %A Stephen J. Gordon %A Warren P. Seering %T Accuracy Issues in Measuring Quantized Images of Straight Line Features %B BOOK28 %K AI07 %A C. K. Cowan %A R. C. Bolles %A M. J. Hannah %A J. A. Herson %T Edge Chain Analysis for Object Verification %B BOOK28 %K AI06 %A Rashpal S. Ahluwalia %A Lynn M. Fogwell %T A Modular Approach to Visual Servoing %B BOOK28 %K AI07 %A Melvin Montemerlo %T NASA's Robotics and Automation Technology Development Program %B BOOK28 %K AI07 AA27 %A Chung Fong %A A. K. Bejczy %A R. Dotson %T Distributed Microcomputer Control System for Advanced Teleoperators %B BOOK28 %K AI07 AA27 H03 %A Bernard Espiau %T An Integrated Experiment in Advanced Nuclear Teleoperation %B BOOK28 %K AI07 %A Fumio Miyazaki %A shigaki Matsubayashi %A Takashi Yoshimi %A Suguru Arimoto %T A New Control Methodology toward Advance Teleoperation of Master Salve Robot Systems %B BOOK28 %K AI07 %A K. Youcef-Toumi %A H. Asada %T The Design of Open Loop Manipulator Arms with Decoupled and Configuration Invariant Inertia Tensors %B BOOK28 %K AI07 %A B. W. Mooring %A T. J. Pack %T Determination and Specification of Robot Repeatability %B BOOK28 %K AI07 %A Vincent Hayward %T Fast Collision Detection Scheme by Recursive Decomposition of a Manipulator Workspace %B BOOK28 %K AI07 %A Vladimir J. Lumesky %T Continuous Path Planning for a Three-Dimensional Cartesian Robot Arm %B BOOK28 %K AI07 AI09 %A Martin Herman %T Fast, Three-Dimensional, Collision-Free Motion Planning %B BOOK28 %K AI07 AI09 %A R. K. Culley %A K. G. Kempf %T A Collision Detection Algorithm Based on Velocity and Distance Bounds %B BOOK28 %K AI07 %A Richard E. Smith %A Maria Gini %T Robot Tracking and Control Issues in an Intelligent Error Recovery System %B BOOK28 %K AI07 %A Marco Somalvico %T The Role of White Collar Robots Real-Time Expert Systems with Multi-Media Sensory Systems %B BOOK28 %K AI07 AI01 O03 %A V. Dupourque %T Using Abstraction Mechanisms to Solve Complex Tasks Programming in Robotics %B BOOK28 %K AI07 %A M. L. Hornick %A B. Ravani %T Data Structure and Database Design for Model Driven Robot Programming %B BOOK28 %K AI07 %A John W. Roach %A Jeff S. Wright %T Spherical Dual Images: A 3D Representation Method for Solid Objects that Combines Dual Space and Gaussian Spheres %B BOOK28 %K AI07 %A Erick P. Krotkov %A Jean Paul Martin %T Range From Focus %B BOOK28 %K AI06 %A Christopher Bania %A James C. Lin %T Theory and Implementation of a High Capacity 3-D Recognition System %B BOOK28 %K AI06 %A A. Robert de Saint Vincent %T A 3D Perception System for the Mobile Robot Hilare %B BOOK28 %K AI07 AA19 AI06 %A Michael J. Smith %T Sociotechnical Considerations in Robotics and Automation %B BOOK28 %K AI07 O05 %A George Burri %A Martin G. Helander %T Case Studies of Human Factors/Ergonomic Design in Robotics and Automation at IBM %B BOOK28 %K AI07 O01 %A Olov Ostberg %T A European Perspective on Human Factors Aspects of Robotics and Automation %B BOOK28 %K AI07 O01 GA03 %A Dennis Bering %T Supervisory Interface with Expert Systems for Semi-Autonomous Walking Robots %B BOOK28 %K AI07 O01 AI01 %A S. V. Nageswara Rao %A S. S. Iyengar %A C. C. Jorgenson %A C. R. Weisbin %T Concurrent Algorithms for Autonomous Robot Navigation in an Unexplored Terrain %B BOOK28 %K AI07 AI06 AA19 H03 %A J. L. Olivier %A F. Ozguner %T A Navigation Algorithm for an Intelligent Vehicle with a Laser Rangefinder %B BOOK28 %K AI07 AI06 AA19 %A Alberto Elfes %T A Sonar-Based Mapping and Navigation System %B BOOK28 %K AI07 AI06 AA19 %A Shriar Negahdaripour %T Direct Passive Navigation: Analytical Solutions for Planes and Curves Surfaces %B BOOK28 %K AI07 AI06 %A Kye Y. Lim %A Masour Eslami %T Robust Adaptive Controller Designs for Robot Manipulator Systems %B BOOK28 %K AI07 %A Steven Fortune %A Gordon Wilfgong %A Chee Yap %T Coordinated Motion of Two Robot Arms %B BOOK28 %K AI07 %A Pierre Tournassoud %T A Strategy for Obstacle Avoidance and its Application to Multi-Robot Systems %B BOOK28 %K AI07 %A Yuan F. Zheng %A Fred R. Sias,\ Jr. %T Multiple Robot Arms in Assembly %B BOOK28 %K AI07 AA26 %A Sohail S. Houssani %A David E. Jakopac %T Multiple Manipulators and Robotic Workcell Coordination %B BOOK28 %K AI07 AA26 %A Matt Barth %A Srinivasan Parthasarathy %A Jing Wang %A Evelyn Hu %A Susan Hackwood %A Gerardo Beni %T A Color Vision System for Microelectronics: Application to Oxide Thickness Measurements %B BOOK28 %K AI07 AI06 %A Ren C. Luo %A Wen-Hsiang Tsai %T Object Recognition Using Tactile Image Array Sensors %B BOOK28 %K AI07 AI06 %A Kenneth J. Overton %A Vivek V. Badami %T Tactile Sensors for Robotic Touch %B BOOK28 %K AI07 AI06 %A M. R. Driels %T Pose Estimation Using Tactile Sensor Data for Assembly Operation %B BOOK28 %K AI07 %A J. Schneiter %A T. B. Sheridan %T Optimal Strategy for Object Recognition by Tactile Sensing %B BOOK28 %K AI07 %A P. Dario %A M. Bergamasco %A A. Fiorillo %A R. Di Leonardo %T Geometrical Optimization and Design Criteria for Tactile Sensing Patterns %B BOOK28 %K AI07 %A S. A. Stansfield %T Primitives, Features and Exploratory Procedures: Building a Robot Tactile Perception System %B BOOK28 %K AI07 AI06 %A R. E. Ellis %T A Multiple-Scale Measure of Static Tactile Texture %B BOOK28 %K AI07 %A David Siegel %A Inaki Garabieta %A John M. Hollerbach %T An Integrated Tactile and Thermal Sensor %B BOOK28 %K AI07 %A J. Vranish %T (I) Magneto-Inductive Skin for Robots %B BOOK28 %K AI07 %A T. Tsumura %T Survey of Automated Guided Vehicle Use in Japanese Factories %B BOOK28 %K AI07 GA01 AA26 AA19 %A T. Tsumura %A M. Hashimoto %T Positioning and Guidance of Ground Vehicle by use of Laser and Corner Cube %B BOOK28 %K AI07 AA19 %A K. Nishide %A M. Hanawa %T Automatic Position Findings of Vehicle by means of Laser %B BOOK28 %K AI07 AA19 %A T. Takeda %T Automated Vehicle Guidance using Video-Camera/spot Mark System %B BOOK28 %K AI07 AA19 %A Kenneth Salisbury %T Teleoperator Hand Design Issues %B BOOK28 %K AI07 %A Jeffrey R. Kerr %T Special Grasping Configurations with Dextrous Hands %B BOOK28 %K AI07 %A Van-Duc Nguyen %T Constructing Force-Closure Grasps %B BOOK28 %K AI07 %A Peter W. Taylor %T Design and Implementation of a Multi-Variable Programmable Controller for a 9-axis General Purpose Gripper %B BOOK28 %K AI07 %A J. Y. S. Luh %A Y. F. Zheng %T Compliance and Coordinated Control of Two Moving Robots %B BOOK28 %K AI07 %A O. Khatib %T A Unified Approach for Motion and Force Control: The Operational Space Formulation %B BOOK28 %K AI07 %A J. J. E. Slotine %T Robustness and Adaptation in Compliant Motion Control %B BOOK28 %K AI07 %A Tsuneo Yashikawa %T Dynamic Hybrid Position/Force Control of Robot Manipulators: Description of Hand Constraints and Calculation of Joint Driving Force %B BOOK28 %K AI07 %A Freidrich Pfeiffer %A Ranier Johanni %T A Concept for Manipulator Trajectory Planning %B BOOK28 %K AI07 %A Bernard Faverjon %T Object Level Programming of Industrial Robots %B BOOK28 %K AI07 %A Bruce H. Krogh %A Charles E. Thorpe %T Integrated Path Planning and Dynamic Steering Control for Autonomous Vehicles %B BOOK28 %K AA19 %A D. Gaw %A A. Meystel %T Minimum Time Navigation of an Unmanned Mobile Robot in a 2 1/2 D World with Obstacles %B BOOK28 %K AA19 AI09 %A A. Meystel %A A. Guez %A G. Hillel %T Planning of Minimum Time Motion Among Obstacles %B BOOK28 %K AI07 AI09 AA19 %A J. Bradley Chen %A Ronald S. Fearing %A Brian S. Armstrong %A Joel W. Burdick %T NYMPH: A Multiprocessor for Manipulation Applications %B BOOK28 %K AI07 H03 %A Christopher G. Atkenson %A Joe McIntyre %T Robot Trajectory Learning Through Practice %B BOOK28 %K AI07 AI04 %A Sanjiv Singh %A Meghanad D. Wagh %T Robot Path Planning Using Intersecting Convex Shapes %B BOOK28 %K AI07 AI09 %A D. M. Lyons %T Tagged Potential Fields: An Approach to Specification of Complex Manipulator Configurations %B BOOK28 %K AI07 %A B. John Oommen %A Irwin Reichstein %T On the Problem of Translating an Elliptic Object Through a Workspace of Elliptic Obstacles %B BOOK28 %K AI07 %A James H. Graham %A John H. Meegher %A Stephen J. Derby %T A Safety and Collision Avoidance System for Industrial Robots %J IEEE Transactions on Industry Applications %V 22 %N 1 %D JAN-FEB 1986 %K AI07 %A K. Piasecki %T On the Bayes Formula for Fuzzy Probability Measures %J Fuzzy Sets and Systems %V 18 %N 2 %D MAR 1986 %K O04 %A I. A. Kalynev %T A Decentralized System for Planning and Controlling the Activity of a Team of Mobile Robots %J Cybernetics %V 21 %N 4 %D JUL-AUG 1984 %P 533-538 %K AI07 AI09 %A B. R. Boyce %T Questions Natural Language Examples in Caduceus %J OnLine %V 10 %N 2 %D MAR 1986 %P 54-76 %K AA01 AI01 AI02 AA14 %A B. S. Thompson %A C. K. Sung %T The Design of Robots and Intelligent Manipulators Using Modern Composite Materials %J MAG24 %P 471-482 %K AI07 %A S. M. Song %A K. J. Waldron %A G. L. Kinzel %T Computer-Aided Geometric Design of Legs for a Walking Vehicle %J MAG24 %P 587-596 %K AI07 %A N. Nandhakumar %A J. K. Aggarwal %T The Artificial Intellgience Approach to Pattern Recognition - A Perspective and an Overview %J MAG25 %P 383-390 %K AI06 %A J. H. Justice %A D. J. Hawkins %A G. Wong %T Multidimensional Attribute Analysis and Pattern Recognition for Seismic Interpretation %J MAG25 %P 391-408 %K AI06 AA03 %A P. L. Love %A M. Simaan %T Segmentation of a Seismic Section Using Image Processing and Artificial Intelligence Techniques %J MAG25 %P 409-420 %K AI06 AA03 %A K. Y. Huang %A K. S. Fu %T Syntactic Pattern Recognition for the Recognition of Bright Spots %J MAG25 %P 421-428 %K AI06 %A K. Y. Huang %A K. S. Fu %A T. H. Sheen %A S. W. Cheng %T Image Processing of Seismograms: (A) Hough Transformation for the Detection of Seismic Patterns (B) Thinning Processing in the Seismogram %J MAG25 %P 429-440 %K AI06 AA03 %A R. F. Kubichek %A E. A. Quincy %T Statistical Modeling and Feature Selection for Seismic Pattern Recognition %J MAG25 %P 441-448 %K AI06 AA03 %A R. F. Kubicheck %A E. A. Quincy %T Identification of Seismic Stratigraphic Traps Using Statistical Pattern Recognition %J MAG25 %P 449-458 %K AI06 AA03 %A H. H. Liu %T A Rule-Based System for Automatic Seismic Determination %J MAG25 %P 459-464 %K AI06 AA03 %A J. C. Hassab %A C. H. Chen %T On Constructing An Expert System for Contact Localization and Tracking %J MAG25 %P 465-474 %K AI06 AA03 underwater acoustics %A R. C. Hughes %A J. N. Maksym %T Acoustic Signal Interpretation: Reasoning with Nonspecific and Uncertain Information %J MAG25 %P 475-484 %K AI06 AA03 O04 %A C. H. Chen %T Recognition of Underwater Transient Patterns %J MAG25 %P 485-490 %K AI06 %A B. Bentz %T Automatic Programming System for Signal Processing Applications %J MAG25 %P 491 %K AA08 AI06 %A Shigemi Nagata %A Tohio Matsura %A Hidachi Endo %T Automatic Recognition System for Logic Circuit Diagrams %J Fujitsu Scientific and Technical Journal %V 21 %N 4 %D AUG 1985 %P 408-420 %K AI06 AA04 %A Yishai A. Feldman %T A Decidable Propositional Dynamic Logic with Explicit Probabilities %J MAG26 %P 11-38 %K O04 AI11 %A David Harel %A Dexter Kozen %T A Programming Language for the Inductive Sets and Applications %J MAG26 %P 118 %A R. I. Phelps %T Artificial Intelligence-An Overview of Similarities with O. R. %J MAG27 %P 13-20 %A M. J. Russell %A R. K. Moore %A M. J. Tomlinson %T Dynamic Programming and Statistical Modeling in Automatic Speech Recognition %J MAG27 %P 21-30 %K AI05 %A Michael Tso %T Network Flow Models in Image Processing %J MAG27 %P 31-34 %K AI06 %A Jon Warwick %A Bob Phelps %T An Application of Dynamic Programming to Pattern Recognition %J MAG27 %P 35-40 %K AI06 %A T. J. Grant %T Lessons for O. R. from A. I.: A Scheduling Case Study %J MAG27 %P 41-48 %K AA05 %A V. G. Sigillito %T Artificial Intelligence Research at the APL Research Center: An Overview %J MAG28 %P 15-18 %A B. F. Kim %A J. Bohandy %A V. G. Sigillito %T A Hierarchical Computer Vision Programming %J MAG28 %P 19-22 %K AI06 %A B. I. Blum %A V. G. Sigillito %T An Expert system for Designing Information Systems %J MAG28 %P 23-30 %K AI01 AA08 %A B. W. Hamill %A R. L. Stewart %T Modeling the Acquisition and Representation of Knowledge for Distributed Tactical Decision Making %J MAG28 %P 31-38 %K AA18 H03 %A Zuo L. Cao %A Sung J. Oh %A Ernest L. Hall %T Dynamic Omnidirectional Vision for Mobile Robots %J MAG29 %P 5-18 %K AI06 AI07 %A Wei-Chung Lin %A Joseph B. Ross %A Michelle Ziegler %T Semiautomatic Calibration of Robot Manipulator for Visual Inspection Task %J MAG29 %P 19-40 %K AI06 AI07 %A K. C. Gupta %A G. J. Carlson %T On Certain Aspects of the Zero Reference Position Method and its Application to an Industrial Manipulator %J MAG29 %P 41-58 %K AI07 %A T. H. Chiu %A A. J. Koivo %A R. Lewczyk %T Experiments on Manipulator Gross Motion Using Self-tuning Controller and Visu al Information %J MAG29 %P 59-70 %K AI07 AI06 %A A. A. Goldenberg %A A. Bazerghi %T Contribution to Synthesis of Manipulator Control %J MAG29 %P 71-104 %K AI07 %A Shuhei Aida %A Mitsuhiko Hasegawa %A Taizo Ueda %T Technology and Corporate Culture of Industrial Robots in Japan %J MAG29 %P 105 %K AI07 GA01 O05 %A A. Micho %T Developments in Expert Systems by M. J. Coombs %J Proceedings of the IEEE %V 74 %N 3 %D MAR 1986 %P 52 %K AT07 AI01 %A J. O. Eklundh %A L. Kjelidahl %T Computer Graphics and Computer Vision -- Some Unifying and Discriminating Features %J Computer and Graphics %V 9 %N 4 %P 339-350 %D 1985 %K AI06 %A John Sandor %T Octree Data Structures and Perspective Imagery %J Computers and Graphics %V 9 %N 4 %D 1985 %K AI06 %A Joseph Y. Halpern %A Yoram Moses %T Toward a Theory of Knowledge and Ignorance (Preliminary Report) %B BOOK36 %P 459-476 %K AI16 %A Asher Peres %T Reversible Logic and Quantum Computers %J Physics Reviews A %V 32 %D 1985 %N 6 %P 3266-3276 %A G. G. Ananiashviii %A Z. I. Mundzhishvii %A N. N. Bichashvii %T Word Identification in a Natural Language in Interactive Systems %J Soobshch. Akad. Nauk. Gruzin. SSR %V 116 %D 1984 %N 3 %P 497-500 %K AI02 %X in Russian with English and Georgian Summaries %A Dumitru Dumitrescu %T Hierarchical Classification with Fuzzy Sets %R Reprint 84-5 %I Univ. Babes-Bolyai %C Cluj-Napoca %D 1984 %K O04 O06 %X also appeared in Seminar of Models, Structures and Information Processing, Cluj-Napoca %A V. V. Krasnoproshin %A V. A. Obratsov %T Two-Level Models of Pattern Recognition Algorithms %J Zh. Vychisl. Mat. i. Mat. Fiz %V 25 %D 1985 %N 10 %P 1534-1546, 1582 %K AI06 %X (in Russian) %A A. M. Slinko %T Some Algebraic Operations Over Classification Algorithms and Their Application %J Zh. Vychisl. Mat. i. Mat. Fiz. %V 25 %D 1985 %N 10 %P 1547-1546 %K O06 %X (in Russian) %A Ronald R. Yager %T Aggregating Evidence Using Quantified Statements %J Inform. Sci %V 36 %D 1985 %N 1-2 %P 179-206 %K O04 %A A. S. Dzyuba %T Mean Deviation of the Frequency of Incorrect Pattern Recognition from the Probability %J Zh. Vychisl. Mat. i. Mat. Fiz. %V 25 %D 1985 %N 10 %P 1547-1546 %K AI06 %X (in Russian) %A D. M. Gabbay %T Theoretical Foundations for Nonmonotonic Reasoning in Expert Systems %B BOOK36 %P 439-457 %K AI15 AI16 %A Brian R. Gaines %A Mildred L. G. Shaw %T Logic, Algebra and Databases %S Computers and Their Applications %V 29 %I Ellis Horwood %C Chichester %K AT15 AA09 %X 294 pages ISBN 0-85312-709-3 %A H. Guggenheimer %T Optical Flow for General Transformations %S Polytechnic Notes on Artificial Intelligence %V 1 %I Polytechnic Institute of New York, Division of Computer Science %C Farmingdale, NY 1985 %K AI06 %X 19 pages %A Abraham Lempel %A Jacob Ziv %T Compression of Two-Dimensional Images %B BOOK37 %P 141-154 %K AI06 %A Can Isik %A Alexander Meystel %T Decision Making at a Level of a Hierarchical Control for Unmanned Robot %B BOOK28 %K AI07 %A Marcin Banachiewicz %T MSL: Robotic Sensor/Effector Programming Language %B BOOK28 %K AI07 %A Michael K. Brown %T On Ultrasonic Detection of Surface Features %B BOOK28 %K AI07 AI06 %A B. A. Auld %A A. J. Bahr %T A Novel Multifunctional Robot Sensor %B BOOK28 %K AI07 %A P. P. Lin %A P. Datseris %T Development of a Position and Force Sensor for Robotic Applications %B BOOK28 %K AI07 %A F. W. Sinden %A R. A. Bole %T A Planar Capactive Force Sensor with Six Degrees of Freedom %B BOOK28 %K AI07 %A William I. Bullers %T Logic Programming for Manufacturing System Specification %B BOOK28 %K AI10 AA26 %A Rodger Cliff %T Meta-Architectural Issues of the ALV: Developing a Paradigm for Intelligent System Engineering %B BOOK28 %K AI07 AA19 %A David Payton %T A Reflexive Control Approach to Autonomous Vehicle Navigation %B BOOK28 %K AI07 AA19 %A Daryl T. Lawton %A Tod Levitt %A Jay Glicksman %T Terrain Modeling and Recognition for an Autonomous Lank Vehicle (sic) %B BOOK28 %K AI07 AA19 AI06 %A Don Shapiro %A Ted Linden %A Jay Glicksman %A Daryl Lawton %T Object Based Planning for an Autonomous Land Vehicle %B BOOK28 %K AI07 AA19 AI09 %A W. W. W. Cimino %A G. R. Penrock %T Workspace of a Six Revolute Decoupled Robot Manipulator %B BOOK28 %K AI07 %A Bayliss McInnis %A Chen-Kang Liu %T Coordinate Frames, Transformations and Inverse Functions for Joint Variables in Robotics: A Tutorial Based Upon Classical Concepts %B BOOK28 %K AI07 %A Dieter W. Wloka %T Simulation of Robots Using CAD-System Robsim %B BOOK28 %K AI07 %A Chi-hau Wau %A Herando Valenco %T Trajectory Feasibility Study Based on Cartesian Workspace Geometry for Robot Manipulators %B BOOK28 %K AI07 %A J. Korein %A R. Taylor %A G. Maier %A L. Durfee %T A Configurable Environment for Motion Programming and Control %B BOOK28 %K AI07 %A Richard Paul %A Hang Zhang %T A Force and Motion Server for Distributed Robot Control %B BOOK28 %K AI07 H03 %A D. Siegel %A S. Narasimhan %A K. Biggers %A G. Gerpheide %T Implementation of Control Methodologies on the Computational Architecture for the Utah/MIT Hand %B BOOK28 %K AI07 %A Robert D. Gaglianello %A Howard P. Katseff %T A Distributed Computing Environment for Robotics %B BOOK28 %K AI07 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 10 06:53:24 1986 Date: Tue, 10 Jun 86 06:53:11 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #146 Status: RO AIList Digest Tuesday, 10 Jun 1986 Volume 4 : Issue 146 Today's Topics: Literature - Bibliography #3 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Bibliography #3 %T Large-Dictionary, On-Line Recognition of Spoken Words %I Helsinki Univ. of Technology %D 1983 %R PB84-214246/CAO %K AI02 %X NTIS price, PC$11.50/MF$6.50 %T LispKit Manual. Volume 1 %I Oxford University %D 1983 %R PB84-204874/CAO %K T01 %X NTIS price PC $17.50/MF $17.50 %T LispKit Manual. Volume 2 (Sources) %I Oxford University %D 1983 %K T01 %R PB84-204882/CAO %X NTIS price PC$17.50/MF $17.50 %T Verification of Secure Systems %I Newcastle upon Tyne Univ. %D 1982 %R PB84-138718/CAO %K AA08 %X NTIS price PC$13.50/MF$13.50 %T Designing Automated Systems -- Need Skill Be Lost %I University of Manchester Institute of Science and Technology %D AUG 1983 %R PB84-232297/CAO %K O05 %X NTIS price PC $9.50/MF $9.50 %T Robot Manipulators: Program Control 1975- SEPT 1984 %I NTIS %R PB 84-875384/CAO %K AI07 AT09 %X NTIS prices PC $40.00/MF$40.00 contains over 300 references extracted from the INSPEC database %T Robotic Technology: An Assessment and Forecast %I DHR, Inc. %C Washington, DC %D JUL 1984 %R AD-A146 672/CAO %K AI07 %X NTIS price PC $17.50 MF $4.50 %T Robotic Safety %I Sandia National Labs %C Alburquerque, NM %D MAY 1984 %R DE84-012237/CAO %K AI07 %X NTIS prices PC $7/MF$4.50 %A Chanderjit Bajaj %T An Efficient Parallel Solution for Euclidean Shortest Paths in Three Dimensions %B BOOK28 %K O06 %A P. Morasso %A F. A. Mussa-Ivaldi %T The Role of Physical Constraints in Natural and Artificial Manipulation %B BOOK28 %K AI07 %A S. Dubowsky %A M. A. Norris %A Z. Shiller %T Time Optimal Trajectory Planning for Robotic Manipulators with Obstacle Avoidance: A CAD Approach %B BOOK28 %K AI07 AI09 %A E. Dombre %A A. Fournier %A C. Quaro %A P. Borrel %T Trends in CAD/CAM Systems for Robotics %B BOOK28 %K AI07 %A A. L. Pai %A K. Lee %A K. Palmer %A D. G. Selvidge %T Automated Visual Inspection of Aircraft Engine Combustor Assemblies %B BOOK28 %K AI06 AA26 %A Thomas M. Kisko %A Eginhard J. Muth %T Multiple-Stage Assembly of Personal Computers in Robotic Workcells with Vision Support %B BOOK28 %K AI07 AI06 AA26 %A E. B. Silverman %A R. K. Simmons %A F. E. Gelhaus %A J. Lewis %T Surveyor: A Remotely Operated Mobile Surveillance System %B BOOK28 %K AI07 AI06 AA19 AA04 %A Edward N. Scheibel %A Henry R. Busby %A Kenneth J. Waldron %T Design of a Mechanical Proximity Sensor %B BOOK28 %K AI07 %A Corinne C. Ruokangas %A Michael S. Black %T Integration of Multiple Sensors to Provide Flexible Control Strategies %B BOOK28 %K AI07 AI06 %A Keishi Hanahara %A Tsugito Maruyama %A Takashi Uchiyama %T High-Speed Hough Transform Processor and its Applications to Automatic Inspection and Measurement %B BOOK28 %K AI06 %A H. D. Cheng %T VLSI Architecture for Dynamic Time-Warp Recognition of Hand-Written Symbols %B BOOK28 %K AI06 %A E. Hu %A S. Mangiaracina %A M. Peters %A A. Harkin %A S. Hackword %A G. Beni %T Inference in Intelligent Machines: Applications to a Thermal Evaporator %B BOOK28 %K AA05 AI01 %A Zixing Cai %A K. S. Fu %T Robot Planning Expert Systems %B BOOK28 %K AI07 AI01 %A Zixing Cai %T Some Research Works on Expert Systems in AI Course at Purdue %B BOOK28 %K AI01 AT18 %A Jean Patrick Tsang %A Yves Lagoude %T Representation and Manipulation of Process Plans in Generic Expert Systems %B BOOK28 %K AI01 AA05 AI09 %A Mark Thomas %T ALV Reasoning Systems %B BOOK28 %K AA19 %A David Morgenthaler %T ALV Perception System %B BOOK28 %K AA19 AI06 %A Jim Lowrie %A R. Douglass %T Autonomous Road Following %B BOOK28 %K AI07 AA19 AI06 %A T. Kanade %T Panel Discussion: Possibilities in ALV Research %B BOOK28 %K AA19 %A Joseph Y. Halpern %T Reasoning About Knowledge: An Overview %B BOOK38 %K AA16 %T Theoretical Aspects of Reasoning About Knowledge %A Joseph Y. Halpert %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1986 %K AA16 AT15 %X ISBN 0-934613-0404 $18.95 %A Ryszard S. Michalski %A Jaime G. Carbonell %A Tom M. Mitchell %T Machine Learning : An Artificial Intelligence Approach, Volume II %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1986 %K AI04 AT15 %X ISBN 0-934613-00-1 $39.95 738 pages %A Ronald J. Brachman %A Hector J. Levesque %T Readings in Knowledge Representation %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1986 %K AA16 AT15 %X ISBN 0-934613-01-X $26.95 571 pages %A Perry L. Miller %T A Critiquing Approach to Expert Computer Advice: Attending %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1984 %K AI01 AA01 anesthesiology O01 AT15 O01 %X ISBN 0-273-08665-0 $19.95 112 pages %A Richard Korf %T Learning to Solve Problems by Searching for Macro-Operators %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1985 %K AI09 AI04 AT15 %X ISBN 0-273-08690-1 $22.95 %A Pual R. Cohen %T Heuristic Reasoning About Uncertainty An Artificial Intelligence Approach %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1985 %K O06 AT15 %X ISBN 0-273-08667-7 $22.95 %A Andrew J. Palay %T Searching with Probabilities %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1985 %K AT15 chess AI03 AA17 O04 %X ISBN 0-273-08664-2 $22.95 192 pages %A Yuichi Ohta %T Knowledge-Based Interpretation of Outdoor Natural Color Scenes %I Morgan Kaufman Publishers, Inc. %C Palo Alto, CA %D 1985 %K AT15 AI06 %X ISBN 0-273-08673-1 $19.95 %A Susanne P. Graf %A J. Sifakis %T From Synchronization Tree Logic to Acceptance Model Logic %B BOOK35 %P 128-142 %K AA08 %A A Sam Kamin %T A FASE specification of FP %B BOOK35 %P 143-152 %K AA08 %A R. Koymans %A R. K. Shyamasundar %A W. P. de Roever %A R. Gerth %A S. Arun-Kumar %T Compositional Semantics for Real-Time Distributed computing %B BOOK35 %P 167-189 %K AA08 %A F. Kroger %T On Temporal Program Verification Rules %J RAIRO Inform. Theor %V 19 %D 1995 %N 3 %P 261-280 %K AA08 %A J. L. Lassez %A Michael John Maher %T Optimal Fixed Points of Logic Programs %J Theoretical Computer Science %V 39 %D 1985 %N 1 %P 15-25 %K AI10 %A Daniel Leivant %T Partial-Correctness Theoreis as First-Order Theories %B BOOK35 %K AA08 AI11 %P 190-195 %A Albert R. Meyer %A Mitchell Wand %T Continuation Semantics in Typed Lambda-Calculi %B BOOK35 %K AA08 %A B. Mishra %A E. Clarke %T Hierarchical Verification of Asynchronous Circuits Using Temporal Logic %B BOOK35 %K AA04 %A Eugene C. Freuder %T A Sufficient Condition for Backtrack-Bounded Search %J JACM %V 32 %N 4 %D 1985 %P 755-761 %K AI03 %A Irina Bercovici %T Unsolvable Terms in Typed Lambda Calculus with Fixed Point Operators %B BOOK35 %P 16-22 %K AA08 %A Val Breazu-Tannen %A Albert R. Meyer %T Lambda Calculus with Constrained Types %B BOOK35 %P 23-40 %K AA08 %A Stephen D. Brookes %T An Axiomatic treatment of a Parallel Programming Language %B BOOK35 %P 41-60 %K AA08 %A A A. Ya Dikovskii %T Solution in Linear Time of Algorithmic Problems Connected with Synthesis of Nonlooping Programs %J Programmirovanie %V 1985 %N 3 %P 38-49 %K AA08 %X in Russian %A E. Allen Emerson %T Automata, Tableaux and Temporal Logics %B BOOK35 %P 79-88 %K AA08 %A Nissim Francez %A Orna Grumberg %A Shmuel Katz %A Amir Pnueli %T Proving Termination of Prolog Programs %B BOOK35 %P 89-105 %K AA08 O02 %A J. Padget %T Current Developments in Lisp %B BOOK39 %P 45-57 %K T01 %A A. W. Biermann %T Algorithmic Methods in Automatic Programming %B BOOK39 %P 124-135 %K AA08 %A G. Kreisel %T Proof Theory and the Synthesis of Progrmas - Potentials and Limitations %B BOOK39 %P 136-150 %K AA08 %A T. Coquand %A G. Huet %T Constructions - A Higher Order Proof System for Mechanizing Mathematics %B BOOK39 %P 151-184 %K AA13 %A C. A. R. Hoare %T The Mathematics of Programming %B BOOK40 %P 1-18 %K AA08 %A G. Agha %A C. Hewitt %T Concurrent Programming Using Actors - Exploiting Large-Scale Parallelism %B BOOK40 %P 19-40 %K H03 %A C. Ghezzi %A D. Mandrioli %A A. Tecchio %T Program Simplification via Symbolic Interpretation %B BOOK40 %P 116-128 %K AA08 %A J. Hsiang %A M. Srivas %T PROLOG Based Inductive Theorem Proving %B BOOK40 %P 129-149 %K T02 AI11 %A J. Veenstra %A N. Ahuja %T Deriving Object Octree from Images %B BOOK40 %P 196-211 %K AI06 %A Z. Manna %A R. Walding %T Deduction with Relation Matching %B BOOK40 %P 212-224 %K AI14 AI11 %A F. V. Jensen %A K. G. Larsen %T Recursively Defined Domains and their Induction Principles %B BOOK40 %P 225-245 %K AA08 %A G. Venkatesh %T A Decision Method for Temporal Logic Based on Resolution %B BOOK40 %P 272-289 %K AI11 AI14 %A A. Chandra %T Who Needs to Verify Programs if you Can Test Them %B BOOK40 %P 346 %K AA08 %A V. A. Saraswat %T Partial Correctness Semantics for CP [Down-and] %B BOOK40 %P 347-368 %K AA08 %A E. W. Stark %T A Proof Technique for Rely Guarantee Properties %B BOOK40 %P 369-391 %K AA08 AI11 %A G. Winskel %T A Complete Proof System for SCCS with Modal Assertions %B BOOK40 %P 392-410 %K AA08 %A R. D. Schraft %A J. Schuler %T Robot Applications in FMS %B Flexible Manufacturing Systems %E H. J. Warnecke %E R. Steinhilper %I Springer-Verlag %C Berlin %D 1985 %A A. A. Goldenberg %A A. Bazerghi %T Synthesis of Robot Control for Assembly Processes %J Mechanism and Machine Theory %V 21 %N 1 %D 1986 %P 43-62 %K AI07 AA26 %A H. J. Warnecke %A B. Frankenhauser %T Assembly of Flexible Parts with Industrial Robots %J MAG30 %P 8-11 %K AI07 AA26 %A P. Nicolaisen %T Improved Worker Safety in the Programming of Industrial Robots %J MAG30 %P 12-14 %K AI07 %A K. H. Wurst %A M. Bauder %T Control Structures and Information Exchange for Linked Industrial Robots %J MAG30 %P 15-17 %K AI07 H03 %A Jeffrey Kerr %A Bernard Roth %T Analysis of Multifingered Hands %J MAG31 %P 3-17 %K AI07 %A Mark L. Hornick %A Bahram Ravani %T Computer Aided Off-Line Planning and Programming of Robot Motion %J MAG31 %P 18-31 %K AI07 %A John Hopcroft %A Gordon Wilfgong %T Motions of Objects in Contact %J MAG31 %P 32-46 %K AI07 %A Katsutoshi Kuribayashi %T A New Actuator of a Joint Mechanism Using TiNi Alloy Wire %J MAG31 %P 47-58 %K AI07 %A Jorge Angeles %T Iterative Kinematic Inversion of General Five-Axis Robot Manipulators %J MAG31 %P 59-70 %K AI07 %A James P. Trevelyan %a Peter D. Kovesi %A Michael Ong %A David Elford %T ET: A Wrist Mechanism without Singular Positions %J MAG31 %P 71 %K AI07 %A K. G. Kempf %T Manufacturing and Artificial Intelligence %B BOOK41 %P 1-20 %K AA26 %A P. Raulefs %T Knowledge Processing Expert Systems %B BOOK41 %P 21-32 %K AI01 %A W. Wahlster %T Cooperative Access Systems %B BOOK41 %P 33-46 %K AI16 %A C. W. Burckhardt %T The Next Generation of Robots - Increased Flexibility Through the Use of Sensors %B BOOK41 %P 47-50 %K AI07 %A B. Neumann %T Vision Systems - State of the Art and Prospects %B BOOK41 %P 51-62 %K AI06 %A G. Albers %T Expert Systems and Knowledge Engineering - Robotics and Intelligent Interfaces - Summary of Discussions %B BOOK41 %P 63-66 %K AI01 AI07 %A B. Rees %T Artificial Intelligence in a Large-Scale Enterprise - the Experience of Digital Equipment Corrporation %B BOOK41 %P 67-76 %A D. Sagalowicz %T Expert Systems in Service Sectors - Use of Expert Systems in 6 Sample Cases %B BOOK41 %P 77-80 %K AA06 AI01 %A H. Thompson %T Office Automation - A Field for Applied Artificial Intelligence %B BOOK41 %P 81-86 %K AA06 %A C. J. Jenny %T Requirements on Expert Systems as Seen by an Insurance Company %B BOOK41 %P 87-96 %K AI01 AA06 %A G. Eibl %T Current Work on Expert Systems and Natural Language Processing at Siemens %B BOOK41 %P 97-106 %K AI01 AI02 %A W. Sieber %T Computer Assisted Synthesis - a Project of the Chemical Industry %B BOOK41 %P 107-110 %K AA16 AA05 %A R. L. Langley %T A Case Study of the Dipmeter Advisor Development %B BOOK41 %P 111-118 %K AA03 AI01 %A S. E. Savory %T FF - A Nixdorf Expert System for Fault-Finding and Fault Finding - An Outline Description %B BOOK41 %P 119-128 %K AI01 AA21 %A J. F. Hery %T A Prototype Expert System in PWR Power Plant Conducting %B BOOK41 %P 129-134 %K AA05 %A H. Marchand %T Knowledge Engineering in CAE - First Industrial Experiences %B BOOK41 %P 135-142 %K AA05 %A J. C. Latombe %T Advanced Information Processing in Robotics %B BOOK41 %P 143-160 %K AA05 %A D. C. Schwartz %T The Lisp Machine Architecture %B BOOK41 %P 161-168 %K H02 %A K. Wiig %T Market Trends in Artificial Intelligence in the United States and Japan %B BOOK41 %P 169-184 %K GA01 GA02 AT04 %A A. W. Pearson %T Speculations on the Future of Knowledge Engineering in Europe I,II %B BOOK41 %P 185-188 %K GA03 %A H. W. Husch %A E. Staudt %T The Influence of Artificial Intelligence on Organizational Structure and Rati onalization %B BOOK41 %P 189-200 %K O05 %A T. Bernold %T Possibilities and Limitations of Artificial Intelligence %B BOOK41 %P 205-208 %K AI16 %A S. A. Cerri %T Problems of the Infrastructure - the Bottlenecks in Research and Training %B BOOK41 %P 209-212 %K AT19 %A B. Oakley %T Research Policy of Administrations - Great Britain (ALVEY) %B BOOK41 %P 213-218 %K AT19 GA03 %A H. Gallaire %A W. Bibel %A B. Oakley %T Cooperation Between University, Government and Industry %B BOOK41 %P 217-220 %K AT10 %A M. Boden %T Artificial Intelligence and Natural Man %B BOOK41 %P 221 %K AI16 O05 %A Benjamin W. Wah %A Guo-Jie Li %T Tutorial: Computers for Artificial Intelligence Applications %I IEEE Computer Society %D MAY 1986 %K AT15 %X list price $49.00 member price $36.00 order no CZ706 ISBN 0-8186-0706-8 648 pages %A A C. S. George Lee %A R. C. Gonzalez %A K. S. Fu %T Tutorial: Robotics (Second Edition) %I IEEE Computer Society %D APRIL 1986 %K AI07 AT15 %X Order NO. CZ658, ISBN 0-8186-0658-4 list price $70.00 member price $39.00 744 pages %A Rama Chellappa %A Alexander A. Sawchuk %T Tutorial: Digital Image Processing and Analysis Volume 2: Digital Image Analysis %I IEEE Computer Society %D DEC 1985 %K AI06 AT15 %X ISBN 0-8186-0666-5 Order No. CZ666 list price $66.00 member price $36.00, 680 pages %A Rama Chellappa %A Alexander A. Sawchuk %T Tutorial: Digital Image Processing and Analysis Volume I: Digital Image Processing %I IEEE Computer Society %D JUN 1985 %K AI06 AT15 %X ISBN 0-8186-0665-7 order No. CZ665 list price $66.00 member price $36.00 736 pages %A J. Gauvin %T Robots 10 Stresses Integration %J MAG32 %P 53-58 %K AI07 %A J. P. Ziskovsky %T Robots - A Piece of the Automation Pie %J MAG32 %P 14 %K AT12 AA26 AI07 %A N. S. Rajaram %T Artificial Intelligence: Its Impact on the Process Industries %J MAG33 %P 33-44 %K AA20 AA16 %A G. Allmendinger %T AI: Can Performance Match the Promise? %J MAG33 %P 45-50 %K AA16 %A R. S. Shirley %A D. A. Fortin %T Developing an Expert System for Process Fault Detection and Analysis %J MAG33 %P 51-56 %K AA05 AA20 AA21 AI01 %A A. E. Nisenfeld %A M. A. Turk %T Batch Reactor Control: Could an Expert Advisor Help? %J MAG33 %P 57 %K AA05 AA20 AI01 %A G. Spur %A G. Seliger %A T. V. Diep %T Sensor Based Assembly System %J MAG34 %P 3-8 %K AI07 AA26 %X (in German) %A U. Vongunten %A C. W. Burckhardt %T Sensors for Robots - Searching, Touching, Grasping %J MAG34 %P 9-16 %K AI07 AI06 %X (in German) %A G. Zimmer %A B. Hosticka %T Integration of Sensors Using VLSI Technologies %J MAG34 %P 17-26 %K AI07 %X (in German) %A W. Weber %A H. Britwieser %T Control of Servomanipulator by the Inverse Model %J MAG34 %P 27-36 %K AI07 %X (in German) %A U. Ahrens %A G. Drunk %A A. Langen %T Sensor Interfaces of Robot Control Systems %J MAG34 %P 37-46 %K AI07 %X (in German) %A G. Pritschow %A G. Gruhler %T Sensors for Geometry and Processing of Sensor Data for Automatical Robot Programming %J MAG34 %P 47-54 %K AI07 AI06 %X (in German) %A T. J. Doll %T Non-Tactile Sensors for Robots and Planning of Sensor Application %J MAG34 %P 55 %K AI07 AI06 %X (in German) %A M. C. Wanner %T Industrial Robots in Japan in 1984 %J MAG34 %P 54 %K AI07 GA01 %X (in German) %T VAl-II, a New Robot Programming Language %J MAG34 %P 63 %K AI07 %X (in German) %A L. A. Walils %A A. Bendell %T Human Factors and Sampling Variation in Graphical Identification and Estimation for the Weibull Distribution %J Reliability Engineering %V 13 %N 3 %D 1985 %K AI08 %A C. A. J. Braganca %A P. Sholl %T Val-II, A Language for Hierarchical Control of a Robot-Based Automated Factory %J MAG35 %P 265-272 %K AI07 AA26 %A P. T. Rayson %T A Review of Expert Systems Principles and Their Role in Manufacturing Systems %J MAG35 %P 279 %K AI07 AA26 AT08 %A W. E. Red %A Hung-Viet Truong-Cao %T Configuration Maps for Robot Path Planning in Two Dimensions %J MAG36 %P 292-298 %K AI07 AI09 %A O. Z. Maimon %A S. Y. Nof %T Coordination of Robots Sharing Assembly Tasks %J MAG36 %P 299-307 %K AI07 AA26 %A S. N. Singh %A A. A. Schy %T Robust Trajectory Following Control of Robotic Systems %J MAG36 %P 308-315 %K AI07 %A A. J. Kolvo %T Self-Tuning Manipulator Control in Cartesian Base Coordinate Systems %J MAG36 %P 316-323 %K AI07 %A G. W. Kohler %T Power Manipulators %J MAG37 %P 195-202 %K AI07 %A U. Ahrens %T Possibilities and Problems in Application of Airborne Ultrasonic Sensors in Assembly Systems and Handling Systems %J MAG37 %P 203-210 %K AI06 AI07 AA26 %A D. Wloka %A K. Blug %T Simulation of Robot Dynamics with the Method of Kane %J MAG37 %P 211-216 %K AI07 %A M. C. Wanner %A K. Baumeister %A G. W. Kohler %A H. Walze %T Robotics in Civil Engineering %J MAG37 %P 227-236 %K AI07 AA05 %A C. Blume %A B. Heck %T Analysis of Inherent Concurrency in High Level Programming Languages for Industrial Robots %J MAG37 %P 237-230 %K AI07 H03 %A P. Nitezki %T Experience with SPIDER- A Portable Subroutine Library for Image Processing %J MAG37 %P 231-233 %K AI06 %A R. Dillmann %A M. C. Wanner %T The Esprit Project in the Area of Robotics %J MAG37 %P 234 %K GA03 AI07 %A Robert L. Stewart %A Douglas R. Ousborne %T An Experimental Expert Weapon Detection System %J Naval Engineers Journal %V 98 %N 3 %D MAY 1986 %P 24-34 %K AA18 AI01 %A M. Raghaven %A S. I. Mehta %A U. Pathie %A K. V. Vaishampayan %T Mechanical Design of an Industrial Robot %J Indian Journal of Technology %V 24 %N 3 %D MAR 1986 %P 149-152 %K AI07 %A Mark Wynott %T Close-Up: Artificial Intelligence Provides Real-Time Control of Material Handling Process %J Industrial Engineering %V 18 %N 4 %D APR 1986 %P 34-46 %K AA26 AA05 O03 %A M. C. Golumbic %A M. Markovich %A S. Tsur %A U. J. Schild %T A Knowledge Based Expert System for Student Advising %J IEEE Transactions on Education %V 29 %N 2 %D MAY 1986 %P 120-124 %K AA06 AI01 %A A. B. Ritter %A W. Braun %A A. Stein %A W. Duran %T Visualization of the Coronary Microcirculation Using Digital Image Processing %J Computers in Biology and Medicine %V 15 %N 6 %D 1985 %P 361-375 %K AI06 AA10 %A D. Umphress %A G. Williams %T Identity Verification Through Keyboard Characteristics %J MAG38 %P 263-274 %K AI06 %A R. J. Baron %T Visual Memories and Mental Images %J MAG38 %P 275-312 %K AI08 %A B. A. Julstrom %A R. J. Baron %T A Model of Mental Imagery %J MAG38 %P 313 %K AI08 %A J. Bajon %A M. Cattoen %A S. D. Kim %T A Concavity Characterization Method for Digital Objects %J Signal Processing %V 9 %N 3 %D OCT 1985 %K AI06 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Wed Jun 11 00:49:38 1986 Date: Wed, 11 Jun 86 00:49:30 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #147 Status: R AIList Digest Tuesday, 10 Jun 1986 Volume 4 : Issue 147 Today's Topics: Literature - Bibliography #4 ---------------------------------------------------------------------- Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Bibliography #4 %A V. M. Kushkov %T Improving the Reliability of Flexible Manufacturing Systems %J MAG19 %K AA26 %A V. N. Abrarov %T Investigation of the Limiting Characteristics of Electrostatic Gripping Devices in Robot Technology %J MAG19 %K AI07 %A D. R. Kritskii %A V. Ya Naimanov %T A Simulation Model for Assessing the Positioning Time of a Robot %J MAG19 %K AI07 %P 45-49 %A V. G. Ostapchuk %T The Use of Image Recognition Systems for Automatic Workpiece Gauging %J MAG19 %K AI07 %P 40-41 %A Kit Grindley %T Applying Expert Principles to Computer Systems Development %J MAG20 %K AI01 AA08 %P 10-14 %A Russell Jones %T European Expert Systems Projects for Systems Developers %J MAG20 %K AA08 AI01 GA03 %P 15-17 %A Sol J. Greenspan %A Alexander Borgida %A John Mylopoulos %T A Requirements Modeling Language and its Logic %J MAG21 %P 9-24 %A Jose Fiadeiro %A Amilcar Sernadas %T The INFOLOG Linear Tense Propositional Logic of Events and Transactions %J MAG21 %P 61-86 %A S. E. Fahlman %T Parallel Processing in Artificial Intelligence %J Parallel Computing %V 2 %N 3 %D DEC 1985 %P 283-286 %K H03 %A F. Neilson %T Abstract Interpretation of Denotational Definitions (A Survey) %B BOOK29 %P 1-20 %K AA08 %A E. A. Emerson %A C. L. Lei %T Temporal Reasoning Under Generalized Fairness Constraints (Extended Abstract) %B BOOK29 %K AA08 %P 21-36 %A M. A. N. Abdallah %T Ions and Local Definitions in Logic Programming %B BOOK29 %P 73-86 %K AI10 %A Adrian Walker %T Knowledge Systems: Principle and Practice %B MAG22 %P 2-13 %K AT08 %A R. L. Ennis %A J. H. Griesmer %A S. J. Hong %A M. Karnaugh %A J. K. Kastner %A D. A. Klein %A K. R. Milliken %A M. I. Schor %A H. M. Van Woerkom %T A Continuous Real-Time Expert System for Computer Operations %J MAG22 %P 14-28 %K AA08 O03 %A P. Hirsch %A W. Katake %A M. Meier %A S. Snyder %A R. Stillman %T Interfaces for Knowledge-Base Builders' Control Knowledge and Application-Specific Procedure %J MAG22 %P 29-38 %A Franz Guenthner %A Hubert Lehmann %A Wolfgang Schonfel %T A Theory for the Representation of Knowledge %J MAG22 %P 39-56 %A John F. Sowa %A Eileen C. Way %T Implementing a Semantic Interpreter Using Conceptual Graphs %J MAG22 %P 57-69 %A Jean Fargues %A Marie-Claude Landau %A Anne Dugourd %A Laurent Catach %T Conceptual Graphs for Semantics and Knowledge Processing %J MAG22 %P 70-79 %A Ghica van Emde Boas %A Peter van Emde Boas %T Storing and Evaluating Horn-Caluse Rules in a Relational Database %J MAG22 %P 80-92 %K AA09 AI10 %A William F. Eddy %A Gabriel P. Pei %T Structures of Rule-Based Belief Functions %J MAG22 %P 93-101 %K AI01 %A H. Diel %A N. Lenz %A H. M. Welsch %T An Experimental Computer Architecture Supporting Expert Systems and Logic Programming %J MAG22 %P 102 %K AI01 AI10 %A T. Williams %T Image Processors Allow Hardware Reconfiguration to Match Applications %B MAG23 %P 46-54 %K AI06 %A W. E. Suydam %T AI Becomes the Soul of the New Machines %J MAG23 %P 55-62 %A D. A. Gewirtz %T Artificial Intelligence As a System Component %J MAG23 %P 63-64 %A A. D. Jacobson %T The Challenges Facing Expert Systems Technology %J MAG23 %P 65-67 %A R. Moore %T AI Must Cater to Nonexperts %J MAG23 %P 68-76 %K O01 %A P. Haley %A C. Williams %T Expert System Development Requires Knowledge Engineering %J MAG23 %P 83-90 %K AI01 %A R. D. Schraft %A J. Schuler %T Robot Applications in FMS %B Flexible Manufacturing Systems: International Trends in Manufacturing Technology %E H. J. Warnecke %E R. Steinhilper %I Springer Verlag %K AA26 AI07 %X $54.00 ISBN 0-903608-95-2 %A B. Buchberger %T Basic Features and Development of the Critical Pair Completion Procedure %B BOOK30 %K AI14 %P 1-45 %A H. T. Zhang %A J. L. Remy %T Contextual Rewriting %B BOOK30 %K AI14 %P 46-62 %A R. V. Book %T Thue Systems as Rewriting Systems %B BOOK30 %K AI14 %P 63-94 %A F. Otto %T Deciding Algebraic Properties of Monoids Presented by Finite Church-Rosser Thue Systems %B BOOK30 %K AI14 %P 95-106 %A S. S. Cosmadakis %A P. C. Kanellakis %T 2 Applications of Equational Theories to Database Theory %B BOOK30 %K AI14 AA09 AI11 %P 107-123 %A N. D. Jones %A P. Sestoft %A H. Sondergaard %T An Experiment in Partial Evaluation - The Generation of a Compiler Generator %B BOOK30 %K AA08 %P 124-140 %A P. Rety %A C. Kirchner %A H. Kirchner %A P. Lescanne %T Narrower- A New Algorithm for Unification and its Application to Logic Programming %B BOOK30 %K AI10 %P 141-157 %A H. Aitkaci %T Solving Type Equations by Graph Rewriting %B BOOK30 %K AI14 AA08 %P 158-179 %A N. Dershowitz %T Termination %B BOOK30 %K AI14 %P 180-224 %A M. Rusinowitch %T Path of Subterms Ordering and Recursive Decomposition Ordering Revisited %B BOOK30 %K AI14 %P 225-240 %A L. Bachmair %A D. A. Plaisted %T Associative Path Orderings %B BOOK30 %K AI14 %P 241-254 %A D. Detlefs %A R. Forgaard %T A Procedure for Automatically Proving the Termination of a Set of Rewrite Rules %B BOOK30 %K AI14 AI11 %P 255-270 %A C. Choppy %A C. Johnen %T Petrireve Proving Petri Net Properties with Rewriting Systems %B BOOK30 %K AI14 AI11 AA08 %P 271-286 %A S. Porat %A N. Francez %T Fairness in Term Rewriting Systems %B BOOK30 %K AI14 %P 287-300 %A J. Hsiang %T Two Results in Term Rewriting Theorem Proving %B BOOK30 %K AI14 AI11 %P 301-324 %A L. Fribourg %T Handling Function Definitions Through Innermost Superposition and Rewriting %B BOOK30 %K AI14 AI11 AA08 %P 325-344 %A A. Kandrirody %A D. Kapur %A P. Narendran %T An Ideal-Theoretic Approach to Word Problems and Unification Problems over Finitely Presented Commutative Algebras %B BOOK30 %K AI14 AI11 %P 345-364 %A K. Yelick %T Combining Unification Algorithms for Confined Regular Equational Theories %B BOOK30 %K AI14 AI11 %P 365-380 %A A. Fortenbacher %T An Algebraic Approach to Unification Under Associativity and Commutativity %B BOOK30 %K AI14 AI11 %P 381-397 %A S. Arnborg %A E. Tiden %T Unification Problems with One-Sided Distributivity %B BOOK30 %K AI14 AI11 %P 398-406 %A P. W. Purdom %A C. A. Brown %T Fast Many-to-One Matching Algorithms %B BOOK30 %K AI14 AI11 %P 407-416 %A D. Benanav %A D. Kapur %A P. Narendran %T Complexity of Matching problems %B BOOK30 %K AI14 AI11 %P 417-429 %A M. Zaionc %T The Set of Unifiers in Typed Lambda-Calculus as Regular Expression %B BOOK30 %K AI14 AI11 AA08 %P 430 %A Mohan M. Trivedi %A John Gilmore %T Guest Editorial: Applications of AI %J MAG24 %P 331-332 %K AI16 %A David M. McKeown %A Clifford A. McVay %A Bruce D. Lucas %T Stereo Verification in Aerial Image Analysis %J MAG24 %P 333-346 %K AI06 %A W. A. Perkins %A T. J. Laffey %A T. A. Nguyen %T Rule-based Interpreting of Aerial Photographs Using the Lockheed Expert System %J MAG24 %P 356-362 %K AI01 AI06 AA18 T03 %A Leonard P. Wesley %T Evidential Knowledge-Based Computer Vision %J MAG24 %P 363-379 %K AI06 %A Amar Mitiche %A J. K. Aggarwal %T Multiple Sensor Intergration/Fusion Through Image Processing: a Review %J MAG24 %P 380-386 %K AI06 AT08 %A S. M. Haynes %A Ramesh Jain %T Event Detection and Correspondence %J MAG24 %P 387-393 %K AI06 %A Robert N. Nelson %A Tzay Y. Young %T Determining Three-Dimensional Object Shape and Orientation from a Single Perspective View %J MAG24 %P 394-401 %K AI06 %A Arthur V. Forman %A J. Ronald Clark %T Robot Vision System for Depalletizing Steel Cylindrical Billets %J MAG24 %P 402-408 %K AI06 AI07 AA26 %A Larry S. Davis %A Todd R. Kushner %A Jacqueline J. Le Moigne %A Allaen M. Waxman %T Road Boundary Detection for Autonomous Vehicle Navigation %J MAG24 %P 409-414 %K AA19 AI06 AI07 %A John F. Gilmore %A Antonio C. Semico %T Knowledge-Based Approach Toward Developing an Autonomous Helicopter System %J MAG24 %P 415-427 %K AA19 %A Julius T. Tou %T Software Architecture of Machine Vision for Roving Robots %J MAG24 %P 428-435 %K AI06 AI07 %A George R. Cross %T Tools for Constructing Knowledge-Based Systems %J MAG24 %P 436-444 %A Viswanath Subramanian %A Gautam Biswas %A James C. Bezdek %T Document Retrieval Using a Fuzzy Knowledge Based System %J MAG24 %P 445-455 %K AA14 O04 %A S. L. Hardt %A J. Rosenberg %T Developing an Expert Ship Message Interpreter: Theoretical and Practical Conclusions %J MAG24 %P 456-464 %K AI01 %A S. W. Thomas %A R. L. Griffith %A W. R. McDonald %T Improvements in Avalanche-Transistor Sweep Circuitry for Electro-Optic Streak Cameras %J MAG24 %P 465-470 %K AI06 %A R. W. Austin %T Spectral Dependence of the Diffuse Attenuation Coefficient of Light in Ocean Waters %J MAG24 %P 471-479 %K AI06 %A R. L. Cohoon %A C. S. Wright %A W. J. Wiley %A Peter S. Guilfoyle %A E. L. Ligeti %T Acousto-Optic Convolver for Digital Pulses %J MAG24 %P 480-489 %K AI06 %A O. Kafri %A B. Ashkenazi %T Line Thinning Algorithm for Nearly Straight Moire Fringes %J MAG24 %P 495-498 %K AI06 %A John A. Saghri %A Hsieh S. Hou %A Andrew G. Tescher %T Personal Computer Based Image Processing with Halftoning %J MAG24 %P 499-504 %K AI06 H01 %A N. S. Kopeika %A A. N. Sidman %A Its'hak Dinstein %A C. Tarnasha %A R. Amir %A Y. Biton %T How Weather Affects Seeing Through the Atmosphere %J MAG24 %P 505 %K AI06 %A Quan Quan Gao %T Prolog-F System %J Chinese Journal of Computing %V 8 %D 1985 %N 2 %P 152-155 %K T02 %X (in chinese) %A V. N. Vapnik %A T. G. Glazkova %A V. A. Koscheev %A A. I. Mikhal'skii %A A. Ya Chervonenkis %T Algorithms and Programs for Reconstructing Dependencies %J Nauka %D 1984 %X (in Russian) %A Bernd Kramer %T Stepwise construction of Nonsequential Software Systems Using a Net-Based Specification Language %B Advances in Petri Nets %V 188 %S Lecture Notes in Computer Science %I Springer-Verlag %C Berlin-Heidelberg-New York %D 1985 %P 307-330 %K AA08 %A U. W. Lipeck %T Specifying Admissibility of Dynamic Database Behavior Using Temporal Logic %B Information Systems: Theoretical and Formal Aspects %P 145-157 %D 1985 %I North-Holland %C Amsterdam-New York %K AA08 AI10 %A Udo Pletat %T A Graph Theoretic Semantics for Semantic Data Models %B Information Systems: Theoretical and Formal Aspects %P 95-108 %D 1985 %I North-Holland %C Amsterdam-New York %K AI16 %A L. I. Rozonoer %T Supplement to the Paper: "Proving Contradictions in Formal Theories. I" %J Avtomat. i Telemekh. %D 1985 %N 4 %P 172 %K AI11 %X (in Russian) %A L. I. Rozonoer %T Proving Contradictions in Formal Theories %J Automat. Remote Control %V 44 %D 1983 %N 6 %P 781-790 %K AI11 %A V. A. Antonyuk %A N. V. Bulygina %A P. Yu Pyt'ev %T Methods of Morphological Analysis in a Problem of Distinguishing Objects %B BOOK31 %P 83-91 %K AI06 %X (in Russian) %A V. A. Bazhanov %T Godel's Theorem and the Problem of the Relation Between Natural and Artificial Intelligence %B BOOK32 %P 49-59 %K AI16 %X (In Russian) %A Henryk Biesiada %T Modification of Methods for Computing the Growth Function of a Developmental System in the Case of a Complex Start Chain %J Podstawy Sterowania %V 15 %D 1985 %N 1-2 %P 113-135 %A Agneta Eriksson %A Anna Lena Johansson %T Computer Based Synthesis of Logic Programs %B BOOK33 %P 105-115 %K AA08 AI10 O02 %A T. I. Ibragimov %T Cybernetics and Natural Languages %B BOOK32 %P 59-73 %K AI02 %X (in russian) %A I. M. Israilov %T Formulas for Calculating Estimates in Algorithms with Complex Systems of Support Sets %J Zh. Vyschisl. Mat. i. Mat. Fiz %V 25 %D 1985 %N 8 %P 1268-1272 %K AI16 %X (in Russian) %A D. I. Panyushev %A D. K. Tkhabisimov %A D. A. Usikov %A N. G. Chebotarev %T Mathematical Bases for the Construction of Systems of Invariant Criteria in a Pattern Recognition Problem %B BOOK31 %P 11-23 %K AI06 %X (in Russian) %A Marco Belia %A Pierpaolo Degano %A Giorgio Levi %A Enrico Dameri %A Maurizio Martelli %T Applicative Communicating Processes in First Order Logic %B BOOK33 %P 1-14 %K AA08 AI11 %A Ernesto J. F. Costo %T Automatic Program Transformation Viewed as Theorem Proving %B BOOK33 %P 37-46 %K AA08 AI11 %A Yu. P. Pyt'ev %T Problems of Morphological Analysis of Images %B BOOK31 %P 41-83 %K AI06 %A E. L. Lawler %T The Traveling Salesman Problem %I John Wiley and Sons %C Somerset, NJ %K AT15 %X $64.95 1-90413-9 465 pages %A J. Gold %T Do-It-Your-Self Expert Systems %J Computer Decisions %V 18 %N 2 %D JAN 14, 1986 %K AI01 %A D. Harel %A R. Sherman %T Propositional Dynamic Logic of Flowcharts %J Information and Control %V 64 %N 1-3 %D JAN-MAR 1985 %P 119-135 %K AA08 AI11 %A Esko Ukkonen %T Algorithms for Approximate String Matching %J Information and Control %V 64 %N 1-3 %D JAN-MAR 1985 %P 100-118 %A E. M. Scharf %A N. J. Mandic %T The Application of a Fuzzy Controller to the Control of a Multi-Degree-of-Freedom Robot Arm %B BOOK34 %P 41-62 %K AI07 O04 %A O. Yagishita %A O. Itoh %A M. Sugeno %T Application of Fuzzy Reasoning to the Water Purification Process %B BOOK34 %P 19-40 %K O04 AA05 %A M. Sugeno %A K. Murakami %T An Experimental Study on Fuzzy Parking Control Using a Model Car %B BOOK34 %P 125-138 %K O04 AA19 %A K. Matsushima %A H. Sugiyama %T Human Operators Fuzzy Model in Man-Machine System with a Nonlinear Controlled Object %B BOOK34 %P 175-186 %K O04 AI08 %A H. Zhao %A M. C. Ma %T The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model %B BOOK34 %P 241 %K O04 AA05 %A Immo O. Kerner %T Logical Programming. History and Present Usage %J Elektron. Informationsverarb. Kybernet %J 21 %D 1985 %N 7-8 %P 355-361 %K AI10 %A B. J. Oommen %A M. A. L. Thathachar %T Multiaction Learning Automata Possessing Ergodicity of the Mean %J Information Science %V 35 %N 3 %P 183-198 %K AI12 AI04 %A Ewa Orlowska %T Logic Approach to Information Systems %J Fund. Inform. %V 8 %D 1985 %N 3-4 %P 359-378 %K AA08 AI10 %A Wen Jun Wu %T Some Remarks on Mechanical Theorem-proving in Elementary Geometry %J Acta Math. Sci (English Ed.) %V 3 %D 1983 %N 4 %P 357-360 %K AI11 AA13 %A Vladimir Batagelj %T Notes on the Dynamic Clusters Method %B IV Conference on Applied Mathematics %P 139-146 %D 1985 %X Univer. Split, Split 1985 %A Mirko Khvanek %T A Note on the Computational Complexity of Hierarchical Overlapping Clustering %J Apl. Mat. %V 30 %D 1985 %N 6 %P 453-460 %A E. Yu Kandrashina %T Means of Representing Temporal Information in Knowledge Bases %J Engineering Cybernetics %V 22 %D 1985 %N 6 %P 89-95 %K AI16 %A George J. Klir %T Architecture of Systems Problem Solving %I Plenum Press %C New York-London %D 1985 %K AT15 %X 540 pages ISBN 0-306-41867-3 %A D. V. Kochetkov %T Construction of Correct Pattern Recognition Algorithms in Quasicomplete Models %J Trudy Inst. Vychisl. Mat. Akad. Nauk Gruzin SSR %V 25 %D 1985 %N 2 %P 35-44 %K AI06 %X (in Russian) %A V. E. Vol'fengagen %A V. Ya Yatsuk %T Models and Methods for Representing Knowledge Algebra on Knowledge- Manipulation Frames %J Engineering Cybernetics %V 22 %D 1985 %N 6 %P 79-88 %K AI16 %A V. V. Zadorozhnyi %T Algorithms for Calculating Estimates for Pattern Recognition %J Kibernetika (Kiev) %D 1985 %V 1 %P 103-107 %K AI06 %X (in Russian with English Summary) %A A. N. Chetaev %T Neural Nets and Markov Chains %I Nauka %C Moscow %D 1985 %K AI12 AT15 %X (in Russian with English Summary) %A Irwin R. Goodman %A Hung T. Nguyen %T Uncertainty Models for Knowledge Based Systems. A Unified Approach to the Measurement of Uncertainty %I North Holland %C Amsterdam-New York %D 1985 %K AT15 O01 %A Eugene C. Freuder %T A Sufficient Condition for Backtrack-Bounded Search %J JACM %V 32 %D 1985 %N 4 %P 755-761 %K AI03 %A J. L. Lassez %A Michael John Maher %T Optimal Fixed-Points of Logic Programs %J Theoretical Computer Science %V 39 %N 1 %D 1985 %P 15-25 %K AI10 %A Rama Chellapa %A Shankar Chatterjee %T Classification of Textures using Gaussian Markov Random Fields %J IEEE Transactions Acoust. Speech Signal Process. %V 33 %D 1985 %N 4 %P 959-363 %K AI06 %A I. N. Krupka %A Yu. I. Petunin %A M. Yu Petunina %T Determination of the Similarity of Two Graphic Images by Menas of the Hausdorff Distance %J Kibernetika (Kiev) %D 1985 %N 3%V 1 %P 118-120 %K AI06 %X Russian. English Summary %A V. A. Nepomnyaschii %T Elimination of Loop Invariants in Program Verification %J Programmirovanie %D 1985 %N 3 %P 3-13 %K AA08 %X in Russian %A Van Nguyen %A Alan Demers %A David Gries %A Susan Owicki %T Behavior: a Temporal Approach to Process Modeling %B BOOK35 %P 237-254 %K AA08 %A Van Nguyen %T The Incompleteness of Misra and Chandy's Proof Systems %J Information Processing Letters %V 21 %D 1985 %N 2 %P 93-96 %K AA08 %A Rohit Parikh %A Ashok Chandra %A Joe Halpern %A Albert Meyer %T Equations Between Regular Terms and an Application to Process Logic %J SIAM J. Computers %V 4 %D 1985 %N 4 %P 935-985 %K AI10 %A Alex Pelin %T A Formalism for Treating Equivalence of Recursive Procedures %J RAIRO Inform. Theor. %V 19 %D 1985 %N 3 %P 293-313 %K AI10 %A Paul Walton Purdom %A Cynthia A. Brown %T The Pure Literal Rule and Polynomial Average Time %J SIAM J. Comput %V 14 %D 1985 %N 4 %P 943-953 %K AI14 %A I. Sain %T The Reasoning Powers of Burstall's (Modal Logic) and Pneueli's (Temporal Logic) Program Verification Methods %B BOOK35 %P 302-319 %K AA08 AI10 AI11 %A A. E. Serik %T Some Exact and Approximate Algorithms for Solution of Some Sequencing Problems with Constraints %J Kibernetika (Kiev) %D 1985 %N 3 %P 29-33 %K AI16 %X (Russian with English Summary) %A Kurt Sieber %T A Partial Correctness Logic for Procedures %B BOOK35 %P 320-342 %K AA08 %A A. E. K. Sobel %A N. Soundararajan %T A Proof System for Distributed Processes %B BOOK35 %P 343-358 %K AA08 %A Robert S. Streett %T Fixpoints and Progam Looping: Reductions from the Propositional Mu-Calculus into Propositional Dynamic Logics of Looping %B BOOK35 %P 359-372 %K AA08 AI11 %A S. F. Shapiro %T Electronic Assembly Becoming Dependent on Robotic Tools %J Computer Design %V 25 %N 3 %D FEB 1, 1986 %K AI07 AA04 AA26 %A Douglas C. Willson %T Current Research, Applications Foreshadow AI's Future Impact %J Data Management %V 24 %N 2 %D FEB 1986 %P 18-19 %A Paul V. Besl %A Ramesh C. Jain %T Invariant Surface Characteristics for 3D Object Recognition in Range Images %J Computer Vision, Graphics and Image Processing %V 33 %N 1 %D JAN 1986 %P 33-80 %K AI06 %A Marloes L. P. Van\ Lierop %T Geometrical Transformations on Pictures Represented by Leaf Codes %J Computer Vision, Graphics and Image Processing %V 33 %N 1 %D JAN 1986 %P 81-98 %K AI06 %A Eric P. Krotkov %T Visual Hyperacuity: representation and Computation of High Precision Position Information %J Computer Vision, Graphics and Image Processing %V 33 %N 1 %D JAN 1986 %K AI06 %A G. Eichmann %A L. M. Royfman %T New Algorithm for Transient Suppression for Images Due to Incomplete or Partial Boundary Data %J IEE Proceedings G: Electronic Circuits %V 133 %N 1 %D FEB 1986 %P 27-29 %K AI06 %A L. F. Huggins %A J. R. Burrettt %A D. D. Jones %T Expert Systems - Concepts and Opportunities %J Agricultural Engineering %D JAN-FEB 1986 %V 67 %N 1 %P 21-23 %K AA23 AA05 AI01 %A D. A. Lowther %A C. M. Saldhana %A G. Choy %T The Applications of Expert Systems to CAD in Electromagnetics %J IEEE Transactions on Magnetics %V 21 %N 6 %D 1985 %P 2559-2563 %K AA04 AI01 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 12 18:42:58 1986 Date: Thu, 12 Jun 86 18:42:54 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #148 Status: RO AIList Digest Thursday, 12 Jun 1986 Volume 4 : Issue 148 Today's Topics: Queries - Tools for RSX & Organic Chemistry & Russian Paper on Sequencing Problems & Scheme & Neural Nets & Complexity Theory & Creativity and Analogy & AI and Education ---------------------------------------------------------------------- Date: Mon 9 Jun 86 09:22:49-PDT From: JPENNINO@USC-ECL.ARPA Subject: TOOLS FOR RSX?? Does anyone know of any ai tools/languages that run under RSX other than the two versions of LISP in DECUS? ------------------------------ Date: Tue, 10 Jun 86 13:24 EDT From: John Batali Subject: AI & Organic Chemistry I'd like to find out about any AI projects attempting to hack organic chemistry. I would be interested in information about systems which do inorganic and biochemistry also. I know about DENDRAL. Please reply to me and I will collect results and send them to the list. John Batali BATALI@OZ.AI.MIT.EDU ------------------------------ Date: Tue, 10 Jun 86 11:10 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Russian to English translation I would like to obtain an English translation of: "Some exact and Approximate Algorithms for Solution of Some Sequencing Problems with Constraints", Kibernetika (Kiev), 1985, #3, pp 29-33. The paper is in Russian with an English summary. I do not have a copy of the paper. Any help will be greatly appreciated. Uttam Mukhopadhyay Computer Science Dept. GM Research Labs Warren, MI 48090-9057 (313)575-2105 Net address: mukhop@gmr.com ------------------------------ Date: Tue 10 Jun 86 08:29:38-PDT From: Mark Richer Subject: Scheme, anyone? I have been asked to give advice regarding the appropriateness of using Scheme for a development effort in Intelligent Computer Assisted Instruction. Although this is partly a research effort also, a clear goal is testing and installing the software in high school classrooms. The hardware available to this project is Hewlett-Packward workstations. Admittedly I know little about Scheme. However, my initial reaction is that no advantages Scheme could provide over CommonLisp could offset the disadvantages of using a language without a large user base for the purposes of software development and installation. CommonLisp promises to offer portability (of course there are still problems, e.g., graphics) and a large user community, and has other obvious advantages because of the general acceptance of Lisp in the U.S. AI community. I'd appreciate some feedback from people that are familiar with Scheme, particularly if you have used it for developing a large AI-based system. Can any argument be presented to justify the resources necessary to train people in Scheme and build and maintain a system in this UnCommonLispLike language? In other words, what is so special about Scheme compared to CommonLisp? Mark ------------------------------ Date: 10-Jun-1986 1436 From: cherubini%cookie.DEC@decwrl.DEC.COM Subject: Neural Nets I am interested in doing some modelling using neural nets. Before building the software system myself, I would like to know of any available public domain software systems which implement neural nets, Boltzmann machines, etc. Any pointers would be appreciated. Ralph Cherubini Digital Equipment Corporation ------------------------------ Date: 9 Jun 1986 1735-EDT From: Bruce Krulwich Subject: connectionism/complexity theory June 2nd's issue of Business Week contained an article about connectionist (parallel distributed processing) models. In it it mentioned a Bell Labs project which set up a neural network which solved the traveling salesman problem aproximately but quickly. I'm interested in articles or other information about this project or any other project linking connectionism with complexity theory, ie, connectionist approaches to graph problems or models which solve other "classical" algorithm design problems. Bruce Krulwich ARPAnet: KRULWICH@C.CS.CMU.EDU Bitnet: BK0A%TC.CC.CMU.EDU@CU20B ------------------------------ Date: Tue, 10 Jun 86 14:04 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Creativity and Analogy At a recent talk in Ann Arbor, Roger Schank observed/implied that a distinct characteristic of many creative people is the ability to analogize. My understanding of analogizing is to define transformations between two domains so that entities and relationships in one domain can be mapped into corresponding entities and relationships in the other domain. It appears that the greater the disparity in the "physics" of the two domains, the higher is the creative effort demanded. Not all transformations produce interesting results. Good analogies must be interesting from the perspective of the particular creative activity. Is this model of creativity--making interesting analogies--valid across the spectrum of creative actvities, from the hard sciences (Physics, Chemistry, etc.) to the fine arts (painting, music)? Is there more to creativity than making interesting analogies? I am inclined to believe that making interesting analogies is at the heart of all intelligent activity that is described as creative. Uttam Mukhopadhyay General Motors Research Labs. (313)575-2105 Net address: mukhop@gmr.com ------------------------------ Date: Tue 10 Jun 86 09:38:50-PDT From: Mark Richer Subject: AI and Education questionnaire Below is a questionnaire requesting information from researchers who are interested in the application of Artificial Intelligence in education. If you are working in this area or are interested in this area please look at the questionnaire and fill it out. [...] You can also fill out the questionnaire on-line and return it by email to the address provided below. This questionnaire is part of a larger effort to facilitate communication among researchers in this area. We are also maintaining a list of postal addresses of those people that are interested in joining a special interest group in AI and education. One activity planned is a special interest group meeting at AAAI '86 this August in Philadelphia. An annoucement of this meeting will be forthcoming. AI and Education Questionnaire prepared 10 June 1986 by W. Lewis Johnson and Mark H. Richer Please send your responses to: W. Lewis Johnson USC ISI 4676 Admiralty Way Marina del Ray, CA 90292 or email to JOHNSON@ISI-VAXA.ARPA (1) Name: (2) Institution or Company: (3) Street Address: (4) City, State [or Country], Zip Code: (5) Work Phone(s): (6) E-Mail address(es): (7) Are you interested in membership in an AI and Education group if one is officially formed? (8) What kind of organization(s) are you connected with? (Check one or more) 1. academic research laboratory 2. academic software development center 3. industrial or commercial research laboratory 4. commerical software company 5. educational institution (please explain) 6. government or military research & development 7. other (please specify) (9) Please characterize your interest and involvement in AI and Education. Please check one and elaborate. 1. I am currently building an AI-based instructional system. (Please describe) 2. I am planning to build an AI-based instructional system. (Please describe) 3. I'm not currently planning to build an instructional system, but I want to keep abreast of developments in the field. (Why?) 4. I'm generally curious about the field. (Why?) (10) Please list the subject areas that interest you (e.g., arithmetic, medical diagnosis, auto mechanics, etc.). (11) Is your work targeted to a specific student population? If so, please indicate which. 1. pre-school or elemementary school students 2. junior high school or high school students 3. disabled or special students 4. college students 5. post-graduate or professional students 6. vocational trainees 7. military training 8. industrial training 9. other (please describe) (12) Which do you consider to be among your MOST central interests? 1. authoring tools or environments (general architectures) 2. diagnosis of student errors and misconceptions 3. educational games 4. explanation and knowledge transfer techniques 5. designing curricula that uses AI-based systems 6. interactive video or CD-ROM 7. micro-worlds or learning environments 8. natural language 9. representation and codification of domain knowledge for the purpose of instruction 10. representation and codification of general problem-solving knowledge for the purpose of instruction 11. representation and codification of teaching knowledge for the purpose of instruction 12. student modeling 13. tutorial strategies 14. user-interfaces (including use of computer graphics in general) 15. user-modeling (for explanation, on-line contextual help, user- interfaces) 16. voice recognition/synthesis 17. other (please specify) (13) Which of the following would you like to see a special interest group in AI and Education offer? (0=not important, 1=important, 2=very important) 1. electronic discussion list 2. bibliographic references without abstracts/reviews 3. bibligraphic references with abstracts/reviews 4. annual meeting at AAAI 5. periodic focused workshops 6. high quality feedback on paper drafts, proposals, ideas, etc. 7. job announcements 8. other: ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 17 00:50:37 1986 Date: Tue, 17 Jun 86 00:50:26 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #149 Status: R AIList Digest Monday, 16 Jun 1986 Volume 4 : Issue 149 Today's Topics: Seminars - Possible Worlds Planning (SRI) & Automatic Expert System Induction (NASA Ames) & Learning by Selection (CMU) & Connectionist Knowledge Representation System (CMU) & Object Recognition using Category Models (UPenn) & CODER Information Retrieval (VPI), New Society - Bay Area AI and Education Meeting ---------------------------------------------------------------------- Date: Wed 11 Jun 86 11:27:30-PDT From: Amy Lansky Subject: Seminar - Possible Worlds Planning (SRI) POSSIBLE WORLDS PLANNING Matt Ginsberg (SJG@SAIL) Stanford University 11:00 AM, MONDAY, June 16 SRI International, Building E, Room EJ228 (new conference room) The size of the search space is perhaps the most intractable of all of the problems facing a general-purpose planner. Some planning methods (means-ends analysis being typical) address this problem by encouraging the system designer to give the planner domain-specific information (perhaps in the form of a difference table) to help govern this search. This paper presents a domain-independent approach to this problem based on the examination of possible worlds in which the planning goal has been achieved. Although a weak method, the ideas presented lead to considerable savings in many examples; in addition, the natural implementation of this approach has the attractive property that incremental efforts in controlling the search provide incremental improvements in performance. This is in contrast to many other approaches to the control of search or inference, which may require large expenditures of effort before any benefits are realized. VISITORS: Please arrive 5 minutes early so that you can be escorted up from the E-building receptionist's desk. Thanks! ------------------------------ Date: Thu, 12 Jun 86 00:18:33 pdt From: eugene@AMES-NAS.ARPA (Eugene Miya) Subject: Seminar - Automatic Expert System Induction (NASA Ames) Subject: June 17, 1986, NASA Ames AI Forum, Automatic Induction National Aeronautics and Space Administration Ames Research Center AMES AI FORUM SEMINAR ANNOUNCEMENT SPEAKER: Dr. Peter Cheeseman Information Sciences Office NASA Ames Research Center TOPIC: Automatic Induction of Probabilistic Expert Systems Many have realized that expert systems that make decisions under uncertainty must represent this uncertainty and manipulate it correctly. This cannot be done in general by "symbolic" (i.e. non-numeric) methods or by sprinkling numbers over logical inference, as advocated by many authors in AI. Probability has been proved to be the only consistent inference scheme if uncertainty is represented by a real number. Probabilistic inference requires assessing the effect of ALL the relevant evidence on the hypothesis of interest through ALL the possible chains of inference (rather than establishing a single path from axioms to theorem, as in logic). However, some methods used in probabilistic inference in AI (e.g. Prospector) impose strong constraints on the structure of the information (e.g. conditional independence) or require large amounts of information. The solution to this problem is to use Maximum Entropy to spread the uncertainty over the set of possibilities as evenly as possible consistent with the known information. A computationally efficient method for performing the maximum entropy calculation will be presented as well as a method for extracting the necessary probabilistic information directly from data. The result is a complete probabilistic expert system without using an expert. DATE: Tuesday, TIME: 10:30-11:30 am BLDG. 239 Room B39 June 17, 1986 (Basement Conf. Room) POINT OF CONTACT: Alison Andrews PHONE NUMBER: (415)694-6741 NET ADDRESS: mer.andrews@ames-vmsb.ARPA VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor Reception Building (N-253) or the Security Station near Gate 18. Do not use the Navy Main Gate. Non-citizens (except Permanent Residents) must have prior approval from the Director's Office one week in advance. Submit requests to the point of contact indicated above. Non-citizens must register at the Visitor Reception Building. Permanent Residents are required to show Alien Registration Card at the time of registration. ------------------------------ Date: 12 June 1986 1156-EDT From: Richard Wallstein@A.CS.CMU.EDU Subject: Seminar - Learning by Selection (CMU) The CMU Summer Research Seminar Series continues this Friday, June 13 at 2:30 PM, 7500 WeH with a talk by Geoffrey Hinton on his new research: A New Algorithm for Learning by Selection Imagine a complicated non-linear process that contains specific steps that are controlled by switches which can be on or off. Each switch has a particular stored probability of being on. Using these probabilities, we generate a random combination of switch settings and then run the process and decide whether the result is good or bad. I shall describe a new learning algorithm that uses information about the goodness of the outcomes to revise the stored probabilities associated with the switches. The algorithm is guaranteed to change the switch probabilites in such a way that future random combinations of switch settings are more likely to produce good outcomes. It can be applied to stochastic processes of arbitrary complexity. If each switch is a synapse, it suggests a new model of learning in the cortex. If each switch is an enzyme and its stored probability is the relative frequency of the relevant gene in the gene pool, the learning algorithm is an efficient way of using the information provided by survival to optimize gene frequencies. The extension to optimizing frequencies of gene combinations appears to be feasible. ------------------------------ Date: 11 Jun 86 01:17:06 EDT From: Mark.Derthick@g.cs.cmu.edu Subject: Seminar - Connectionist Knowledge Representation System (CMU) I will present my thesis proposal, "A Connectionist Knowledge Representation System," 2pm Wednesday, June 18, in 5409. I propose to develop a knowledge representation system that is functionally similar to KL2, but implemented on a parallel, non-symbolic architecture. Answering queries is carried out by a Boltzmann Machine network in which concepts, roles, and individuals are represented by patterns of activity of very simple processing units. By choosing good representations, a small network suffices to capture the knowledge as pairwise interactions among the units in the network. A single parallel constraint satisfaction search accomplishes the answering process. I will prove that for any definable knowledge base, the network constructed will answer queries as specified by the formal knowledge level semantics. ------------------------------ Date: Wed, 11 Jun 86 14:05 EDT From: Tim Finin Subject: Seminar - Object Recognition using Category Models (UPenn) OBJECT RECOGNITION USING FUNCTION BASED CATEGORY MODELS Ph. D. Thesis Proposal Franc Solina GRASP Laboratory UNIVERSITY of PENNSYLVANIA Department of Computer and Information Sciences Philadelphia, PA 19104-6389 Phone (215) 898 8298 Net address: franc@upenn We propose a modeling system for recognition of generic objects. Based on the observation that fulfilling of the same function results in similar shapes we will consider object categories that are formed around the principle of functionality. The representation consists of a prototypi- cal object represented by prototypical parts and relations between these parts. Parts are modeled by superquadric volumetric primitives which are combined via boolean opera- tions to form objects. Variations between objects within a category are described by allowable changes in structure and shape deformations of prototypical parts. Each prototypical part and relation has a set of associated features that can be recognized in the images. The recognition process proceeds as follows; the input is a pair of stereo reflec- tance images. The closed contours and sparse 3-D points, the result of low level vision, are analyzed to find domain specific features. These features are used for indexing the model data base to make hypotheses. The selected hypotheses are then verified on the geometric level by deforming the prototype in allowable way to match the data. We base our design of the modeling system upon the current psychological theories of the human visual perception. advisor: R. Bajcsy commitee: N. Badler, H. ElGindy, J. Kender (Columbia University). Time: Monday, June 16, 11 PM, room 216 ------------------------------ Date: Tue, 27 May 86 10:31:37 edt From: vtcs1::fox Subject: Seminar - CODER Information Retrieval (VPI) [Forwarded from IRList Digest V2#26 by Laws@SRI-AI.] The M.S. defense of Robert K. France will be held at 10am Monday June 2 in Norris 301. The title of his thesis is "An Artificial Intelligence Environment for Information Retrieval Research." The CODER (COmposite Document Expert/extended/effective Retrieval) project is a multi-year effort to investigate how best to apply artificial intelligence methods to increase the effectiveness of information retrieval systems. Particular attention is being given to analysis and representation of heterogeneous documents, such as electronic mail digests or messages, which vary widely in style, length, topic, and structure. In order to ensure system adaptability and to allow reconfiguration for controlled experimentation, the project has been designed as a moderated expert system. This thesis covers the design problems involved in providing a unified architecture and knowledge representation scheme for such a system, and the solutions chosen for CODER. An overall object-oriented environment is constructed using a set of message-passing primitives based on a modified Prolog call paradigm. Within this environment is embedded the skeleton of a flexible expert system, where task decomposition is performed in a knowledge-oriented fashion and where subtask managers are implemented as members of a community of experts. A three-level knowledge representation formalism of elementary data types, frames, and relations is provided, and can be used to construct knowledge structures such as terms, meaning structures, and document interpretations. The use of individually tailored specialist experts coupled with standardized blackboard modules for communication and control and external knowledge bases for maintenance of factual world knowledge allows for rapid prototyping, incremental development, and flexibility under change. The system as a whole is structured as a set of communicating modules, defined functionally and imple- mented under UNIX using sockets and the TCP/IP protocol for communication. Inferential modules are being coded in MU-Prolog; non-inferential modules are being prototyped in MU-Prolog and will be re-implemented as needed in C++. Host: Dr. Edward A. Fox, Dept. of Computer Science ------------------------------ Date: Fri 13 Jun 86 11:45:06-PDT From: Mark Richer Subject: New Society - Bay Area AI and Education Meeting Date: 13 Jun 86 10:27 PDT From: dmrussell.pa@Xerox.COM Subject: Bay Area AI and Education Meeting: June 23rd, 6PM, PARC What: Bay Area AI and Education Group holding its first meeting. Where: Xerox Palo Alto Research Center (PARC) 3333 Coyote Hill Rd. Palo Alto, CA (send for detailed directions) When: June 23rd, 6PM Who: Speakers: Jim Greeno and Peter Pirolli "Some New Directions in the Science of Instructional Design" Math Science and Technology Education Dept. University of Calif. Berkeley Host: Daniel Russell Intelligent Systems Lab PARC Amplification: BARRET (Bay ARea Research in Educational Technology) is an attempt to bring together many of the local people working in the area of applying AI to education. There are significant efforts at Berkeley, Stanford, UCSF, SRI, PARC and so on. BARRET is a way of establishing some communication between the various groups, by hosting technical talks on this topic and setting aside time for informal discussion. To do this, BARRET will be implemented as a moving sequence of talks circulating throughout the Bay Area on a (roughly) monthly basis. We hope to have high quality talks on areas of mutual interest to be followed by an equally high-quality dinner that will allow us to meet and discuss topics further. This first meeting of BARRET will be followed by dinner at Chef Chu's, assuming that we can get a reasonable headcount. (With enough warning, non-MSG-ers and veggies can be accomodated.) So, if you are interested in attending, please message (or call) me and let me know of your intentions. That will allow us to do some planning for our first meeting. -- Dan Russell -- ArpaNet: DMRussell.PA@XEROX.COM Phone: (415)-494-4308 Mail: Dan Russell ISL 3333 Coyote Hill Rd. Palo Alto, CA 94304 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jun 17 00:50:53 1986 Date: Tue, 17 Jun 86 00:50:43 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #150 Status: R AIList Digest Monday, 16 Jun 1986 Volume 4 : Issue 150 Today's Topics: Seminars - Modular Construction of Logics for Specification (CMU) & Dependent Types (MIT) & Programming Languages & Temporal Knowledge (Edinburgh), Conference - APS Workshop at AAAI-86 & Temporal Aspects in Information Systems & Symposium on Connectionism ---------------------------------------------------------------------- Date: 10 June 1986 1542-EDT From: Theona Stefanis@A.CS.CMU.EDU Subject: Seminar - Modular Construction of Logics for Specification (CMU) PS SEMINAR Date: Friday, 20 June Time: 10:00 Place: WeH 4605 Modular Construction of Logics for Specification Martin Sadler Imperial College, London mrs@@doc.ic.ac.uk A typical informal presentation of a logic for reasoning about some aspect of computing is: Nice logic = First-order logic + Temporal bit We can ask two questions about this equation. Firstly, what is going on with the '+' and other similar combinators? Secondly, how do we guarantee that such equations are well behaved - in the sense that the logics we build will support the ideas of specification and stepwise refinement? To answer these questions one needs to have a formal framework for talking about logics. Our preference is for a proof theoretic framework. Crudely: Logic "=" presentation of a consequence relation Combinator "=" function of type: logic* -> logic Modularity principle "=" interchange principle between combinators One important kind of combinator that has not received the attention it deserves is a 'talksabout' combinator that gives one a meta-level mechanism with respect to the logic it is applied to. Together with the observation that canon- ical "arrow" logics can be built on the collections of vari- ous kinds of preserving maps between logics, we can start talking about logics as solutions to "logic-equations": LOGIC = talksabout(logic) + talksabout(nice_logic) + talksabout(nice_logic -> implementation_logic) The seminar will attempt to show how such a framework can be used, as part of an interactive environment, to sup- port software engineers in setting up logics for specifica- tion and verification. ------------------------------ Date: Tue 10 Jun 86 14:45:38-EDT From: Lisa F. Melcher Subject: Seminar - Dependent Types (MIT) Date: Thursday, June 19, 1986 Time: 2:45 p.m......Refreshments 3:00 p.m......Lecture Place: NE43 - 512A "DEPENDENT TYPES -- FIFTEEN YEARS LATER" J.Y.GIRARD University of Paris VII Our system F of polymorphic lambda calculus (developed independently by Reynolds) is attracting increasing interest because of its relation to polymorphic types in programming, although our original motivation for studying the system was quite different. In this talk we summarize the basic theoretical properties of the type system and compare the computer scientists' and logicians' views of it. Sponsored by TOC, Laboratory for Computer Science Albert Meyer, Host ------------------------------ Date: Fri, 6 Jun 86 18:00:06 -0100 From: Gideon Sahar Subject: Seminars - Programming Languages & Temporal Knowledge (Edinburgh) EDINBURGH AI SEMINARS Date: Wednesday 28th May l986 Place: Department of Artificial Intelligence Seminar Room Forrest Hill EDINBURGH. Dr. M. Steedman, Centre for Cognitive Sciences and Department of Artificial Intelligence will give a seminar entitled - "Combinators, Universals and Natural Language Processing". Combinators are primitive elements in terms of which we can define the notion of defining a function, as with the lambda operator of LISP, without the use of the bound variables which are associated with that operator, and which are so expensive for interpreters of LISP and related functional programming languages. For some time, my colleagues and I have been arguing that the syntax and semantics of certain problematic "unbounded dependencies" and "reduced" constituents in natural language constructions such as English relative clauses and coordinate constructions can be elegantly captured by extending Categorial Grammars (discussed by Ewan Klein here a couple of months ago) with operations corresponding to certain simple combinators. Such grammars hold out the promise of a theory according to which natural language syntax is a very direct reflection of a computational efficient applicative semantics which minimises the use of bound variables. The paper concerns some implications for processing and the prediction of certain contrasts between the grammars of Spanish and English. Date: Wednesday, 4th June l986 Time: 2.00 p.m. Place: Department of Artificial Intelligence, Seminar Room, Forrest Hill, EDINBURGH. Professor Colin Bell, University of Iowa will give a seminar entitled - ``A Point-Based Representation of Temporal Knowledge in Automated Project Planning". A point-based temporal reasoning system is presented as an alternative to existing interval-based temporal logics. It appears to be especially applicable in nonlinear hierarchical planning where such temporal quantities as activity durations and scheduling delays are uncertain. Temporal constraints representable in this system fall into a very restricted class. However, it is argued that representing more general constraints results in computational intractability. Details of implementation are discussed. Date: Wednesday, 11th June l986 Time: 2.00 p.m. Place: Department of Artificial Intelligence, Seminar Room F10, 80 South Bridge, EDINBURGH. Mr. Peter Jackson, Department of Artificial Intelligence, University of Edinburgh will give a seminar entitled - ``Towards a Methodology for Designing Problem Solving Architectures in the Object-Oriented Style". Although current object-oriented systems provide the programmer with both software modules (such as production rule interpreters and theorem provers) and software tools (such as browsers and debuggers), they fail to provide a set of guidelines as to how to select and combine modules to create a particular architecture. Too often, one is given some combination of Flavors, OPS and Prolog (or their look-alikes), and then left to get on with it. A further criticism is that the modules provided do not lend themselves to adaptation by specialization in the spirit of the object-oriented environment in which they are embedded. A methodology for creating 'abstract architectures', which can be instantiated via a process of specialization, is described in the context of a new object-oriented programming language called SLOOP. A detailed example is given of how to create a generic production rule architecture whose behaviour is easy to modify incrementally, together with a sample problem solving program. It is suggested that certain features of SLOOP, namely its transparency and the fact that it is mostly implemented in itself, make it particularly useful as a vehicle for tasks of this kind, while some of the facilities offered, such as pattern-matched parameter-passing and the ability to compile SLOOP into Lisp and thence into native code, encourage a functional style of programming without extracting too high a price in terms of efficiency. ------------------------------ Date: Thu, 12 Jun 86 15:17:26 edt From: als@mitre-bedford.ARPA (Alice L. Schafer) Subject: Conference - APS Workshop at AAAI-86 ---> The cutoff date for receiving a request for participation in the Workshop on Automatic Programming at the AAAI-86 was accidentally omitted from the notice. While the original date was June 15, we will extend it to June 30 to give people sufficient time to respond. ... The workshop will be held on Thursday August 14th, and will last approximately three hours. The current plan is that one and a half hours will be occupied by brief (seven minutes) presentations of current work, followed by a panel discussion with active audience participation, moderated by Tom Cheatham of Harvard. Due to the size of the available rooms, we may have to limit the audience to researchers who have experience with some aspect of the APS problem. If you wish to present your current work or be on the panel you should send us a 200-800 word abstract. The decision on who will participate will be based on these abstracts. If you wish to participate as a member of the audience instead, send us a short note containing a description of your work or references to pertinent papers you have written. If we need to limit the audience we will base our decisions on these responses, which should be sent by June 30. Please post a printed copy of this notice at your workplace. Organized by: Alice Schafer Richard Brown Richard Piazza (617) 271-2363 (617) 271-7559 (617) 271-2363 als@mitre-bedford.arpa rhb@mitre-bedford.arpa rlp@mitre-bedford.arpa of the Knowledge-Based Automatic Programming Project (ISFI) The MITRE Corporation Mail Stop A-045 Burlington Road Bedford, MA 01730 ------------------------------ Date: Mon, 9 Jun 86 12:06:07 PDT From: Lougie Anderson Reply-to: Lougie Anderson Subject: Conference - Temporal Aspects in Information Systems Conference Announcement TEMPORAL ASPECTS IN INFORMATION SYSTEMS Sophia-Antopolis, France May 13-15, 1987 Temporal Aspects in Information Systems: A working confer- ence by IFIP Technical Committee TC 8 "Information Systems" in cooperation with AFCET, the French Computer Science and Information Society. MOTIVATION Recent developments in the area of information systems emphasize the role played by time. Research in information systems design has pointed to the need for a realistic world model which includes representations not only for snapshot descriptions of the real world, but also for histories, on the evolution of such descriptions over time. These developments still suffer from a lack of concepts, languages and theoretical foundations dealing with the design of tem- poral and behavioral aspects of informations systems. More- over, temporal correctness criteria and analysis are neces- sary. In addition the management of computerized informa- tion systems requires new mechanisms to allow the implemen- tation and the handling of these elements. Papers can be submitted on the following items. TOPICS Theoretical and Modeling Aspects of the Time Dimension of Information: Time theory, temporal logic, causality theory, linguistic and philosophic approaches of time. Time model- ing, behavioral modeling, languages for specification and query, temporal/causal dependencies and constraints, tem- poral consistency checking. Time and Behavior Implementation and Handling: Temporal dimension of databases, historical databases implementation, user interface for historical databases, snapshots, time and behavior handling in computerized systems, time and event mechanisms, management of multiple versions, data time versus transaction time, concurrency and synchronization problems. Applications with a Temporal Dimension: Time in decision support systems for prediction and planning achievement, time dimension in CAD and CAM systems, in large statistical data bases, in large socio-economic data bases, in medical systems, and real-time systems. GENERAL CONFERENCE CHAIRMAN Francois Bodart Institute Notre-Dame de la Paix 21, rue Grangagnage 500 Namur, Belgium PROGRAMME COMMITTEE CHAIRMAN Colette Rolland Universite Paris I 12, place du Pantheon 75231 Paris Cedex, France ORGANIZING COMMITTEE CHAIRMAN Michel Leonard Centre Universitaire d'Informatique Universite de Geneve 24, rue du General-Dufour 1211 Geneve 4, Switzerland PROGRAMME COMMITTEE M. Adiba, IMAG, France J. Allen, University of Rochester, USA L. Anderson, Tektronix, USA V. de Antonellis, University of Milano, Italy G. Ariav, Tel Aviv University, Israel F. Bodart, Institut Notre-Dame de la Paix, Belgium J. Bubenko, University of Stockholm, Sweden J. Clifford, New York University, USA A. Furtado, University of Rio de Janeiro, Brazil M. Jarke, University of Frankfurt, Germany M. Leonard, University of Geneva, Switzerland S. Navathe, University of Florida, USA P. Nobecourt, University Paris I, France A. Olive, University of Barcelona, Spain B. Pernici, Milano Polytechnic School, Italy U. Schiel, Federal University of Paraiba, Brazil A. Sernadas, University of Lisbon, Portugal HOW TO SUBMIT Original papers in English of up to 5,000 words are sought on topics included in, but not limited to, the proposed list. Papers should be recieved before October 1st, 1986. Authors should submit four copies of the full paper to: AFCET TAIS, Conference 156, boulevard Pereire 75017 Paris, France IMPORTANT DATES Papers due: October 1, 1986 Acceptance notification: December 15, 1986 Final copy due: February 15, 1987 Conference: May 13-15, 1987 ------------------------------ Date: 13 JUN 86 11:38-N From: SCHNEIDER%CGEUGE51.BITNET@WISCVM.WISC.EDU Subject: Conference - Symposium on Connectionism Symposium and Workshop on CONNECTIONISM : MULTIPLE AGENTS, PARALLELISM AND LEARNING ================================================================= Symposium 9th of September 1986 Workshop 10th - 12th of September 1986 LOCATION Geneva University, UNI II, Switzerland The symposium and workshop are sponsored by the Swiss Group for Artificial Intelligence and Cognitive Science (SGAICO), the Jean Piaget Foundation and the Faculty of Psychology and Education Science of the University of Geneva. Symposium Programme : SYMPOSIUM DAY : 9TH OF SEPTEMBER At the 9th of September a one day symposium will be held on "CONNECTIONISM : Multiple Agents , Parallelism and Learning" where the main ideas of this paradigm in Artificial Intelligence and Cognitive Science will be presented. The symposium is open to the public. The goal of this symposium is to give an introduction and survey of the problems of Connectionism. 09.00 - 10.30 THE SOCIETY THEORY OF MIND: Marvin Minsky, MIT 10.45 - 12.00 THE LOCALIST POSITION IN CONNECTIONISM: ON REPRESENTATION AND LEARNING Jerome Feldman, University of Rochester 14.00 - 15.15 THE DISTRIBUTIONIST POSITION IN CONNECTIONISM: ON REPRESENTATION AND LEARNING Terry Sejnowski, John Hopkins University 15.30 - 16.45 LEARNING PARADIGMS IN CONNECTIONISM: David Rumelhart, University of California 16.45 - 18.00 BUILDING WORKING CONNECTIONIST MODELS David Waltz, Intelligent Thinking Machines, USA Entry fees for the SYMPOSIUM: STUDENTS: SFRS 40,- ; UNIVERSITY MEMBERS: SFRS 100,- ; INDUSTRY: SFRS 250,- The following persons get a entry-price reduction of 20 Percent: - Members and Students of the Faculty of Psychology and Education Science of the University of Geneva - Members of the Swiss Informatitions Society (SI) - Members of the Swiss Group for Artificial Intelligence and Cognitive Science (SGAICO) For further information and registration apply to the SYMPOSIUM SECRETARY Mrs. Manuela Mounir WORKSHOP PROGRAMME After the Symposium a two and a half day workshop will take place at the Geneva University. The workshop is limited to 20 invited attendees, whose research interests are in different aspects of multiple agents, parallelism and learning. The goal of the workshop is to discuss and elucidate different approaches and their interrelations and to further conceptualise the present problems and future promising research directions in Connectionism. The workshop will be videotaped and later made accessible to a wider audience. Participants are: Guenter Albers Genetic A.I. and Epistemics Lab. Geneva Uni. Andre Boder MIT and Geneva University Heiner Brand University of Bielefeld, Germany Guy Cellerier Genetic A.I. and Epistemics Lab. Geneva Uni. Stefano Cerri Mario Negri Institute, Milan Jean-Jaques Ducret Genetic A.I. and Epistemics Lab. Geneva Uni. Jerome Feldman University of Rochester, Rochester Ken Haase Artificial Intelligence Lab., MIT John Holland University of Michigan, Ann Arbor Marvin Minsky Artificial Intelligence Lab., MIT Rolf Pfeifer Institute for Informatics,Zuerich University Mike Rosner ISSCO, Geneva University Thomas Rothenfluh Conflict Research Center, Zuerich University David Rumelhart University of California, San Diego Terrence Sejnowski John Hopkins University, Baltimore Zoltan Schreter Genetic A.I. and Epistemics Lab. Geneva Uni. Luc Steels A.I. Lab, Free University, Brussels John Sutton GTE Labs, Walton, USA David Waltz Intelligent Thinking Machines, Cambridge USA ORGANISATION: Guenter Albers GENETIC ARTIFICIAL INTELLIGENCE AND EPISTEMICS LABORATORY University of Geneva, Switzerland TEL.: (0041) 22 20 93 33 EXT.2623 (Switzerland) REGISTRATION and SYMPOSIUM SECRETARY: Mrs. Manuela Mounir FACULTY OF PSYCHOLOGY AND EDUCATION SCIENCE, UNIVERSITY OF GENEVA CH-1211 Geneva 4, Switzerland TEL.: (0041) 22 20 93 33 EXT.2657 (Switzerland) Telex: 423801 UNI CH Geneve For further (non-organisation-related) information send mail to Guenter Albers or reply by email to Daniel Schneider: to VMS/BITNET: to UNIX/EAN: (preferable) BITNET: SCHNEIDER@CGEUGE51 shneider%cui.unige.chunet@CERNVAX ARPA: SCHNEIDER%CGEUGE51.BITNET@WISCVM shneider%cui.unige.chunet@ubc.csnet uucp: mcvax!cernvax!cui!shneider X.400/ean: shneider@cui.unige.chunet ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 19 19:16:18 1986 Date: Thu, 19 Jun 86 19:16:13 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #151 Status: R AIList Digest Wednesday, 18 Jun 1986 Volume 4 : Issue 151 Today's Topics: Queries - References on Natural Language & Aristotle & Prolog Optimization & P-Shell & Knowledge Acquisition & Expert Systems for Clinical Neuropsychological Assessment & Expert System Validation and Verification & Expert-Ease & Recursive Fixed-Point Solvers & Cheeseman's Automatic Expert System Induction, Psychology & Physics - Inside Out & Dr. Who ---------------------------------------------------------------------- Date: 2 Jun 86 16:56:00 PST From: seismo!nwc-143b.ARPA!sefai Subject: References on Natural Language??? [Forwarded from IRList Digest V2#26 by Laws@SRI-AI.] I am investigating literature that will hopefully help me on my master's thesis. Without being too specific, the topic centers around schemes for representing natural language in a computer system. So far, my list of references includes: 1. Handbook of Artificial Intelligence, Barr and Feigenbaum 2. NETL: A System for Representing and Using Real-World Knowledge, Fahlman 3. Human Information Processing, Lindsay and Norman 4. A Theory of Syntactic Recognition for Natural Language, Marcus 5. Principles of Artificial Intelligence, Nilsson 6. Basic English (series), Ogden 7. The Cognitive Computer on Language, Schank with Childers 8. Computer Models of Thought and Language, Schank and Colby 9. Artificial Intelligence, Winston 10. A Handbook of English Grammar, Zandvoort I'd appreciate any good references others have come across and I'd be more than happy to send out the list afterwards. Gene Guglielmo sefai@nwc-143b [Note: Thank you for the offer of collecting references. You have quite an unusual assortment of works! I encourage you to look at "Introduction to Modern Information Retrieval" by Salton and McGill and "Information Retrieval, 2nd ed." by C.J. VanRijsbergen for a rather different perspective. Let us know more details of your plans when you become more focused. - Ed] ------------------------------ Date: Sat 7 Jun 86 23:38:21-PDT From: Ali Ozer Reply-to: ali@score,taran@sushi Subject: Curious about Aristotle, "Knowledge Processor"... [Forwarded from the Stanford bboard by Laws@SRI-AI.] In p.19 of June 4 Campus Report, there is a short 2-column article titled "Knowledge processor named Aristotle pays a visit." The article says... "Modeling computer architecture after the human nervous system, a Stanford graduate has developed Aristotle, a unique knowledge processor. ... Modeled on synapses, the junctions between nerve cells, Aristotle encodes information in fundamental units ranging from a single character to a word, then a sentence, and finally a paragraph. ... ``You teach Aristotle like a child,'' he [John Voevodsky, the inventor] said. ``Characters first, then words and sentences.'' ... Aristotle can perform several tasks. It was first trained to turn a light on and off, then to ring a bell, and finally to blow a whistle. ... " Anyway, if you're curious from the above, you should get your hands on a Campus Report and read the whole article. This machine just sounds fascinating, but there isn't any technical information about it in the paper. Does anyone out there know more about this? The article makes it sound like this processor provides an approach to intelligence that could easily replace most of the current AI techniques! But, I don't know much about AI, and I certainly know very little about this Aristotle, so I just don't know... If anyone has more info or knows where there is more written about this "knowledge processor," I would like to hear about it. Very curious about things I should not be curious about during finals week, but am, -Ali ------------------------------ Date: 13 Jun 86 04:25:15 GMT From: sdcsvax!sdcrdcf!burdvax!psuvax1!gondor!hou@ucbvax.berkeley.edu (Po Hou) Subject: A.I.(expert systems) I am studying application of prolog on expert systems. Is the following fact correct ? (1) when a predicate is used recently then it will be used in the future with higher possibility than those predicates that are not used recently. (i.e. it is similar to working set concept of virtual memory.) For example, predicate call p(a,Y,Z) gets a set {(X,Y,Z)| X=a } , then what is the possibility that p(a,Y,Z) is called again ? (2) what is the user behavior to use a expert system ? (3) frequently used knowledge will be used with a higher possibility ? ------------------------------ Date: 13 Jun 86 22:49:29 GMT From: sdcsvax!noscvax!kanemoto@ucbvax.berkeley.edu (Nelson T. Kanemoto) Subject: P-Shell Query I'm looking for information on P-Shell, described in the article: "Programming in P-Shell", by Newton S. Lee, IEEE Expert, pg. 50-63, in the recent Summer 1986 issue. If anyone knows the cost, availability, or any other information concerning P-Shell, please send me a message: kanemoto@nosc.arpa Thanks in advance, Nelson T. Kanemoto Computer Sciences Corporation NOSC Hawaii ------------------------------ Date: Fri, 13 Jun 86 14:52:26-1000 From: Jimmy Y. Cheng Subject: Knowledge Acquisition I'm interested in the knowledge acquisition of the domain knowledge from an expert to an engineer. Can anyone help me in locating an article or reference to people working in this area? Any help would be greatly appreciated. Since this the bottleneck in building an expert system, any progress would be a boon to AI. ------------------------------ Date: 15 Jun 86 17:31:48 GMT From: ucbcad!nike!topaz!harvard!ut-sally!ut-ngp!gknight@ucbvax.berkeley.edu (Gary Knight) Subject: Expert systems for clinical neuropsychological assessment. A few weeks ago I posted an inquiry concerning my interest in the current state of research and development on expert systems for clinical neuropsychological assessment. I received several replies, some of which led to some very useful material. I would now like to re-post that inquiry, seeking still further input from anyone who has such information and did *not* respond before. So . . . Does anyone have information they can share with me on research or development work with respect to expert systems for application to clinical neuro- psychological assessment? If so, please reply by mail and I'll post a summary, including all previous replies. Thanks very much. -- Gary Knight, 3604 Pinnacle Road, Austin, TX 78746 (512/328-2480). Biopsychology Program, Univ. of Texas at Austin. "There is nothing better in life than to have a goal and be working toward it." -- Goethe. ------------------------------ Date: Mon, 16 Jun 86 15:58 ??? From: PENN%NGSTL1%ti-eg.csnet@CSNET-RELAY.ARPA Subject: Expert System Validation and Verification I am doing a literature search on the validation and verification of expert systems. I have found a few articles manually, however, my database searches (INSPEC, COMPENDEX, etc.) haven't been helpful. I am getting more on the use of expert systems to test other computer software than procedures/ methods for validating expert systems! If you have any pertinent information, or some good sources with carry-over potential to expert systems I would appreciate being contacted. In return I will be happy to furnish you with the final literature search information. Thank you! Mary Penn Knowledge Engineer TI-Artificial Intelligence Laboratory (214) 343-7667 P.O. Box 660246 M/S 3645 Dallas, TX 75266 PENN%NGSTL1@TI-EG.CSNET [One validation effort was carried out by John Reiter for the HYDRO expert system (an extension of Prospector that he, Rene Reboh, and John Gashnig developed). Reiter used scattergrams and rank correlations to compare various actual parameters with those predicted by the system. The final SRI report was "Development of a Knowledge-Based Interface to a Hydrological Simulation Program," May 1982, but I believe most of the validation effort was documented in John's dissertation. -- KIL] ------------------------------ Date: 16 Jun 86 18:58:19 GMT From: ihnp4!houxm!mtuxo!mtgzy!jis@ucbvax.berkeley.edu (j.mukerji) Subject: Info wanted on Expert-Ease I just read a glossy on Expert-Ease, which is based on an inference engine developed by Donald Michie at Edinburgh University. I would appreciate any comments about it (good or bad) from anyone who has used it. I am considering buying it, and of course would like to know whether it is all that it is touted to be. If there is sufficient interest I will summerize responses to this message in this newsgroup. Thank you. Jishnu Mukerji AT&T Information Systems Middeltown NJ ihnp4!mtgzz!jis1 ------------------------------ Date: Mon, 16 Jun 86 11:31 EDT From: DSTEVEN%clemson.csnet@CSNET-RELAY.ARPA Subject: Recursive fixed point solvers. We are looking for a program to solve for fixed points of recursive equations. Actually, any help will be greatly appreciated. Thanks in advance Steve (803) 656-5880 ------------------------------ Date: Mon 16 Jun 86 14:00:05-PDT From: Tom Garvey Subject: Re: Seminar - Automatic Expert System Induction (NASA Ames) Does this mean that Cheeseman has at long last implemented something, or is this going to be more of the same old theoretical maximum entropy stuff over high-order probability distributions that would not only eliminate the need for an expert but also make it impossible for the expert to provide the necessary information. Presumably, an expert system with no experts is misnamed, and systems for statistical analysis have been around for a long time. Cheers, Tom ------------------------------ Date: Sat, 7 Jun 86 19:00:43 bst From: gcj%qmc-ori.uucp@Cs.Ucl.AC.UK Subject: Re: Inside Out >From: majka@ubc.CSNET.UUCP >> ...Einstein's theory of general relativity, which models the cosmos >> as a 4 dimensional pseudo-Riemannian spacetime. ... > >*pseudo*-Riemannian? I think you mean Semi-Reimannian, and that applies >to the metric, not the spacetime. > >--- >Marc Majka > OK, take your pick, but it must be a pseudo/semi-Riemannian spacetime, so that you can have null distances; ie the metric on the manifold must have differing signs eg (+1,-1,-1,-1), ie in Minkowski space. (Note that in GR, all spacetimes are locally Minkowski). The manifold must be Hausdorff and differentiable to arbitrary order, ie C-infinity. Apart from differential geometry, the keyword is *model*. Spacetime is not any type of Riemannian manifold. Newton did not need differential geometry to form a model of gravity. Did spacetime suddenly curve when Einstein discovered general relativity? What is interesting is the leap from the intuitive idea of the apple falling because it is `pulled' by the earth, to the non-intuitive idea of the apple falling because nothing holds it up. It falls along a timelike geodesic, the shortest (4-dim) distance between two points. And there is nothing intuitive about quantum chromo-dynamics, at least not to me. Gordon Joly, ARPA: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Fri, 6 Jun 86 14:10 EST From: STANKULI%cs.umass.edu@CSNET-RELAY.ARPA Subject: more inside and out Another response to phayes AILIST vol 4 # 125 and subsequent replies on the intuitions of tardis inside and out... particularly Ken Laws reply. i will include references to relevant episodes which test the limits of tardis functions. the tardis is not a portal to another dimension. Gallifreyan temporal mechanics are particularly limited to our 4-dimensional universe (they call it N-space) in its operation. theoretically the time lords can go to any time and place in N-space but they accept informal constraints they call "time laws" which they try to enforce to lower the occurrence of paradox phenomema. but even the high council of time lords will violate these regulations once in a while at great expense of energy ('the five doctors' peter davidson). the fundamental piece of Gallifreyan technology is called a dimensional stabalizer which was discovered by Omeger and perfected by an engineer called Rasilon. the metauniverse of dr. who is at least five dimensional. there have been times when the doctor's tardis has been transported through accident into other parallel 4D universes where it functions with different precision than in N-space. the doctor (jon pertwee) had this happen once when repairing the tardis console and later the tardis was thrown into E-space by a stellar accident for a number of episodes (tom baker). E-space was a much smaller 4D universe which was collapsing instead of expanding. punching holes in the side of a tardis has happened. in 'terminus' (peter davidson) the tardis was breaking apart in transit and attached to the side of a space vehicle. the doctor and companions came and went from the tardis through an unstable hole in the wall of nyssa's room. the hole acted just like a door, but they could not control its opening and closing. there is no fundamental reason why the inside of a tardis is always larger than the outside. the relative dimensions of inside and out are uncoupled. the 'outer plasmic shell' is controlled by a chameleon circuit and can be any size. the outside could be larger than the inside. tom baker once designed an exterior the size of the pyramid of cheops but since his chameleon circuit was broken, it reverted to the police box. the master once had his tardis materialize around a Concorde SST ('time flight' peter davidson). there is no reason why a tardis outside could not be the size of a shoe box or postage stamp, except that a humanoid could not exit the craft in such case. an error in 'logopolis' (tom baker) caused it to become three feet high, trapping the doctor inside. a tardis can also jettison portions of its interior space in emergency ('castrovalva' peter davidson). some other interesting properties have arisen in the 20+ year series. if a tardis is turned over on its side, there is a control which can rotate the interior so the floor orients with gravity ('time flight'). when a tardis materializes, it incorporates the space it appears in. the master's tardis contained the original SST inside his own. a dimensional anomaly arises when one tardis materializes around another tardis ('logopolis'). the dimensional stabilizer works by folding one dimension into another-- apparently a point-for-point mapping mechanism. they call this 'block transfer computation'. if one tardis incorporates another one, they are both in danger of losing external reference. since they both contain the same folded space, they both contain each other. it is possible to walk from the outer one through the inner one to the outer one... like infinite regression in a hall of mirrors. for one of the longest running dramatic series in history, the BBC staff of writers is to be admired for their conceptual detail in metauniversal design. their spacetime mechanics have interesting and plausible ramifications on a different order of magnitude than purely child fantasy like alice through the looking glass. the limitations of temporal technology, genetic regeneration, metalinguistic translation, and even the sonic screwdriver make the series intriguing beyond the fun of watching. stan ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 19 19:16:41 1986 Date: Thu, 19 Jun 86 19:16:35 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #152 Status: R AIList Digest Wednesday, 18 Jun 1986 Volume 4 : Issue 152 Today's Topics: Policy - AIList Distribution Mechanisms & LISP Messages, Techniques - Lisp and Lazy Evaluation, AI Tools - AI Software for MS-DOS ---------------------------------------------------------------------- Date: 7 Jun 86 20:47:02 GMT From: cad!nike!caip!seismo!rochester!altman@ucbvax.berkeley.edu Subject: AIList Distribution Mechanisms From: Art Altman I read reference to "ailist vol xxx" in mod.ai, but I do not see this ailist appearing in either net.ai or mod.ai. Anyone know - to what network is "ailist" posted? Is it sent to individuals and should I get on some list to receive it? Thanks, Art "altman@rochester" [The distribution currently includes many channels: direct mail (to Arpanet and other networks), exploded digests sent to certain bboard systems, and a hybrid of UUCP mod.ai and net.ai. The first two are in digest form, with volume numbers that let readers track whether issues have been missed or refer to issues by number. There is also a Today's Topics section that previews the digest contents to aid skimming and later text searches. The UUCP distribution lacks these niceties and some of the editing and sorting that I provide as moderator, but offer real-time interchanges. It works as follows. Net.ai is forwarded to my mailbox. I pull out any messages that look pertinent and nontrivial and add them to direct submissions in the AIList mailbox. I select a number of messages and form them into a digest to be sent to the Arpanet readers. Then I delete the net.ai messages from the originals and send the direct submissions in undigested form to mod.ai. The overall effect is that people reading net.ai plus mod.ai get everything in the digest plus any part of the net.ai discussion that I ignore. -- KIL] ------------------------------ Date: Wed, 11 Jun 86 21:02:58 edt From: Jay Weber Reply-to: jay@rochester.UUCP (Jay Weber) Subject: Re: Common LISP style standards I admit that there is a significant overlap between the people interested in Artificial Intelligence and those interested in the LISP programming language, but it should be obvious that articles like "Common LISP style standards" and "LISP for IBM PCs" should be posted to newgroups other than mod.ai, and such newsgroups do exist. This newsgroup has a large amount of traffic, and I expect that many readers have unsubscribed due to the large amount of inappropriate submissions. I would mail this message to individuals who do not realize this, but there have been so many it would not be effective. Mostly this message is to the moderators, who should be enforcing the focus of the newsgroup. Jay Weber Department of Computer Science University of Rochester jay@rochester.arpa [Unfortunately there are few relevant discussion lists on the Arpanet side of the gateway. We do have one on workstations and others on particular micros or Lisps, but nothing of the required generality. I will be glad to help anyone who wants to start a list devoted to Lisp or any other topic currently covered by AIList: Expert Systems AI Techniques Knowledge Representation Knowledge Acquisition Problem Solving Hierarchical Inference Machine Learning Pattern Recognition Analogical Reasoning Data Analysis Cognitive Psychology Human Perception Natural Language Computational Linguistics AI Languages and Systems Machine Translation Theorem Proving Decision Theory Logic Programming Computer Science Automatic Programming Information Science AI & Society Sociology of AI AI & Business AI Workstations (Step forward, folks, or I may burn out soon. Besides, its lots of fun and it puts you in contact with the best people.) -- KIL] ------------------------------ Date: 06-Jun-1986 1604 From: kevin%logic.DEC@decwrl.DEC.COM (Kevin LaRue -- The Earth makes one resolution every 24 hours.) Subject: Re: Lisp & lazy evaluation The bibliographies contained in the two books Henderson, Peter, ``Functional Programming: Application and Implementation,'' Prentice-Hall International, London, 1980. and Darlington, J., Peter Henderson and David A. Turner, editors, ``Functional Programming and its Applications: an Advanced Course,'' Cambridge University Press, Cambridge, 1982. point to the following historical references: Burge, W. H., ``Recursive Programming Techniques,'' Addison-Wesley, Reading, Massachusetts, 1975. Friedman, D. P., and D. S. Wise, `CONS Should Not Evaluate its Arguments,' in ``Automata, Languages and Programming,'' S. Michaelson and R. Milner, editors, Edinburgh University Press, Edinburgh, 1976 Henderson, Peter and J. M. Morris, `A Lazy Evaluator,' in ``Proceedings of the 3rd POPL Symposium,'' Atlanta, Georgia, 1976. Kahn, G., and D. McQueen, `Coroutines and Networks of Parallel Processors,' in ``Information Processing 77'' North-Holland, Amsterdam, 1977. Landin, P. J., `A Correspondence between Algol 60 and Church's Lambda Calculus,' in ``Communications of the ACM'' Volume 8, number 3, pages 158-165, 1965. Vuillemin, J. E., ``Proof Techniques for Recursive Programs,'' Memo AIM-318, STAN-CS-73-393, Stanford University, 1973. You may also want to ask David Turner about his experiences with his ``Miranda'' functional programming environment. Indeed, he is distributing it, if you would like to play with it yourself. His electronic address is: dat%ukc@ucl-cs (He's currently at the University of Kent at Canterbury.) ------------------------------ Date: 9 Jun 86 02:08:13 GMT From: ihnp4!lzaz!psc@ucbvax.berkeley.edu (Paul S. R. Chisholm) Subject: AI software for MS-DOS (long) < cross posted to effected groups; please followup only to net.micro.pc > Here's the third and (I hope) last list of artificial intelligence software for MS-DOS based machines. I started with expert system shells, then picked up Prolog processors, and Lisp and other languages found their way in. "Decision support" tools are presumably decision tree managers; for their relation to expert systems, see the hot and heavy discussion in net.ai and mod.ai (or actually, the summary I've posted to those groups). Thanks to Lou Fried (FRIED@SRI-KL.ARPA) and Dallas Webster (CMP.BARC@R20.UTexas.Edu or ut-sally!batman!dallas) for additions to this list. The names, addresses, phone numbers, and especially prices are not guaranteed to be free from typos, line noise, or obsolescence. I have no experience or further information on any of these packages; don't call me, call the company. On the other hand, if *you* have used any of these systems, please drop me a line; I'll be happy to summarize and repost. I'd also like to hear of any products I'd forgotten, or any errata to my list. -Paul S. R. Chisholm, UUCP {ihnp4,cbosgd,pegasus,mtgzz}!lznv!psc AT&T Mail !psrchisholm, Internet mtgzz!lznv!psc@topaz.rutgers.edu -- Aion Development System: expert system shell, $7000 Aion Corp. 101 University Ave., 4th floor Palo Alto, CA 94301 415-328-9595 The Decision Maker: decision support, $250 Alamo Learning Systems Suite 500, 1850 Mt. Diablo Blvd. Walnut Creek, CA 94596 415-930-8521 Arity Expert System Development Package: expert system shell, $295 Arity Standard Prolog: AI language (Prolog), $95 Arity Prolog Interpreter V4: AI language (Prolog), $350 Arity Prolog Compiler & Interpreter V4: AI language (Prolog), $795 Arity Corp 358 Baker Ave. Concord, MA 01742 617-371-1243 Prdigy: expert system shell, $450 OPS5+: expert system shell, $3000 Artelligence, Inc. 14902 Preston Rd., suite 212-252 Dallas, TX 75240 214-437-0361 A.D.A Educational Prolog: AI language (Prolog), $29.95 VML Prolog: AI language (Prolog), $300 Automata Design Associates 1570 Arran Way Dresher, PA 19025 215-646-4894 Micro In-Ate: expert system shell for fault diagnosis, $5000 Automated Reasoning Corporation 290 West 12th St., Suite 1D New York, NY 10014 212-206-6331 Turbo Prolog: AI language (Prolog), $99.95 Borland International 4585 Scotts Valley Dr. Scotts Valley, CA 95066 408-438-8400 SpinPro: ultracentrifugation experiment expert system [GCLISP], $2500 (note: a specific expert system, *not* a shell!) Beckman Instruments, Inc. Spinco Division 415-857-1150 (sales info); (714)-961-3728 (technical info) Matt Heffron Xsys: expert system shell, $995 California Intelligence 912 Powell St. #8 San Fransisco, CA 94108 415-391-4846 Prolog V: AI language (Prolog), $69.95/$99.95 Chalcedony Software, Inc. 5580 La Jolla Blvd, Suite 126B La Jolla, CA 92037 617-483-8513 Expert Choice: decision support, $495 Decision Support Software Inc. 1300 Vincent Place McLean, VA 22101 703-442-7900 Methods: AI language (Smalltalk), $250 Digitalk, Inc. 5200 W. Century Blvd. Los Angeles, CA 90045 213-645-1082 TOPSCI: expert system shell, $75/$175 Dynamic Master Systems Inc. PO Box 566456 Atlanta, GA 30356 404-565-0771 Decision Analyst: decision support, $139 Executive Software, Inc. Bay St. Shanty Bay, Ontario, CANADA LOL 2LO 705-722-3373 The Idea Generator: decision support, $195 Experience in Software 2039 Sattuck Ave., Suite 401 Berkeley, CA 94704 415-644-0694 ES/P Advisor: expert system shell, $895 Prolog-1: AI language (Prolog), $395 Prolog-2 Interpreter and Compiler: AI Language, $1895 Expert Systems International 1150 First Ave. King of Prussia, PA 19406 215-337-2300 Xi: expert system shell, $795 Expertech Expertech House, 172 Bath Rd. Slough, Berks SLI 3XE, ENGLAND 0753-821321 Portable Software Inc. 650 Bair Island Rd., Suite 204 Redwood City, CA 94063 415-367-6264 (and somebody near Boston at 617-470-2267) Exsys 3.0: expert system shell, $395 (demo disk for $10?) Exsys Inc. PO Box 75158, Contract Sta. 14 Albuquerque, NM 87194 505-836-6676 GEN-X: Expert system shell General Electric Research and Development Center Schenectady, NY 12345 TIMM-PC: expert system shell, $9500 General Research 7655 Old Spring House Rd. McLean, VA 22102 703-893-5900 GCLisp (Golden Common Lisp): AI language (Lisp), $495 286 Developer: AI Language (Lisp), $1195 (expert system shell to be announced in late 1986) (K-base was a specialized proprietary package, now dead) Gold Hill Computers 163 Havard St. Cambridge, MA 02139 617-492-2071 Expert Ease: expert system shell, $695 (example based, forward chaining) Expert Edge: expert system shell, $795 (rule based, backward chaining, uncertainty, math) (they also sell 1st Class for $495, same as Programs in Motion) Human Edge Software 2445 Faber Pl. Palo Alto, CA 94303 CA: 800-824-7325, elsewhere: 800-624-5227 AL/X: Expert system shell ALCS: Expert system shell Inference Manager: expert system shell, 500 pounds Intelligent Terminals Ltd or George House 15 Canal St. 36 North Hanover St. Oxford, UK OX26BH Glasgow, Scotland G1 2AD 041-522-1353 (Try Jeffrey Perrone & Associates, 415-431-9562) Knowol: expert system shell, $39.95/$99.95? Intelligent Machines Co. 3813 N. 14th St. Arlington, VA 22201 703-528-9136 KEE: expert system shell IntelliCorp 1975 El Camino Real W. Mountain View, CA 94040 415-965-5500 Experteach: expert system shell, $475 Intelliware, Inc. 4676 Admiralty Way, Suite 401 Marina del Rey, CA 90291 213-305-9391 IQLisp: AI language (Lisp), $175 Integral Quality 6265 Twentieth Avenue (or POB 31970) Seattle, WA 98115 206-527-2918 Savior: expert system shell, 3000 pounds ISI Limited 11 Oakdene Road Redhill, Surrey, UK RH16BT (0737)71327 Ex-Tran: expert system shell, $3000 Jeffrey Perrone & Associates 415-431-9562 KDS: expert system shell, $795 (development), $150 (playback) KDS II: expert system shell, $945 KDS Corp. 934 Hunter Rd. Wilmette, IL 60091 312-251-2621 Decision Aide: decision support, $250 Trouble Shooter: decision support, $250 Kepner-Tregoe, Inc. PO Box 704 Princeton, NJ 08542 609-921-2806 Insight: expert system shell, $95 Insight2: expert system shell, $485 Level 5 Research 4980 S. Highway A1-A Melbourne Beach, FL 32751 (moved to 503 Fifth Ave., Suite 201, Indiatlantic, FL 32903?) 305-729-9046 Byso Lisp: AI language (Lisp), $125 Levien Instrument Co. Sittlington Hill PO Box 31 McDowell, VA 24458 703-396-3345 Lightyear: decision support, $495 Lightyear, Inc. 1333 Lawrence Expwy., Bldg. 210 Santa Clara, CA 95051 408-985-8811 (may be obsolete; see Thoughtware Inc.) Daisy: expert system shell Lithp Systems BV Meervalweg 72 1121 JP Landsmeer The Netherlands Micro-Prolog: AI language (Prolog), $395 Logic Programming Associates 31 Crescent Drive Milford, CT 06460 203-872-7988 MProlog: AI language (Prolog), $725 Logicware, Inc. 5000 Birch St., West Tower, suite 3000 Newport Beach, CA 92660 416-665-0022 70 Walnut St. Wellesley, MA 02181 617-237-2254?) Reveal: expert system shell, $4500 ($2000?) McDonnell Douglas Knowledge Engineering Products Division 20705 Valley Green Dr. Cupertino, CA 95014 408-446-7406 MicroExpert: expert system shell, $49.95 McGraw-Hill PO Box 400 Hightstown, NJ 08520 or 1221 Avenue of the Americas New York, NY 10020 NY: 212-512-2999, elsewhere 800-628-0004 Guru: integrated software with expert system shell, $3000 Micro Data Base Systems PO Box 248 Lafayette, IN 47902 317-463-2581 muLisp-85: AI language (Lisp), $250 Microsoft Corp. 10700 Northup Way, Box 97200 Bellevue, WA 98004 206-828-8080 Expert-2: expert system shell, $70 (requires MMSFORTH v2.4, $180) Miller Microcomputer Services 61 Lakeshore Rd. Natick, MA 01760 317-653-6136 QTime: expert system shell, $695 MOM Corp. Two Northside 75 Atlanta, GA 30318 404-351-2902 Expert: expert system shell, $100 (same as MMS Expert-2 above? requires Forth?!) Mountain View Press PO Box 4656 Mountain View, CA 94040 415-961-4103 LISP/88: AI language (Lisp), $50 Norell Data Systems PO Box 70127 3400 Wilshire Blvd Los Angeles, CA 90010 213-748-5978 UO-Lisp: AI language (Lisp), $150 Northwest Computer Algorithms PO Box 90995 Long Beach, CA 90809 213-426-1893 ERS: expert system shell PAR Technology Corp. 220 Seneca Turnpike New Hartford, NY 13413 XLISP: AI language (object oriented Lisp), $6 (disk 148) Expert System of Steel: expert system shell, $6 (disk 268) Esie: expert system shell, $6 (disk 398) ADA Public Domain Prolog: AI language (Prolog), $6 (disk 405) (see also Automata Design Associates) PC-SIG 1030 E. Duane Ave, Suite J Sunnyvale, CA 94086 408-730-9291; CA 800-235-6647, elsewhere 800-235-6646 (or where ever you get fine public domain software) Waltz Lisp, $169 ProCode International 15930 SW Colony Place Portland, OR 97224 503-684-3000 OPS83: expert system shell Production Systems Technologies, Inc. 642 Gettysburg St. Pittsburgh, PA 15206 412-362-3117 Micro-Prolog Professional: AI language?, $395 apes: expert system shell [micro-Prolog], $250 Programming Logic Systems 312 Crescent Dr. Milford, CT 06460 203-877-7988 1st-Class: expert system shell, $20/$495 ($250??) Programs in Motion, Inc. 10 Sycamore Rd. Wayland, MA 01778 617-653-5093 Rulemaster/PC: expert system shell, $995 Radian Corp. 8501 Mo-Pac Blvd. PO Box 9948 Austin, TX 78766 512-454-4797 Small-X: expert system shell, $125/$225 RK Software PO Box 2085 West Chester, PA 19380 215-436-4570 Knowledge Engineering System II: expert system shell, $4000 Software Architecture & Engineering 1500 Wilson Blvd., suite 800 Arlington, VA 22209 703-276-7910 Wizdom: expert system shell, $1250/$2050 Software Intelligence Lab 1593 Locust Ave. Bohemia, NY 11716 212-747-9066/516-589-1676 LISP/80: AI language (Lisp), $40 Software Toolworks 15233 Ventura Blvd., Suite 1118 Sherman Oaks, CA 91403 818-986-4885 Xper: expert system shell, $95 Softway 415-397-4666 TransLISP: AI language (Lisp), $75 Prolog-86: AI language (Prolog), $95/$250 Solution Systems 335-P Washington St. Norwell, MA 02061 617-659-1571/800-821-2492 SeRIES-PC: AI language (Lisp), $5000 SeRIes PC: Expert system shell, $15000 SRI International Advanced Computer Systems Division 333 Ravenswood Avenue Menlo Park, CA 94025 415-859-2859; contact Bob Wohlsen, x4408 Q'NIAL: AI language (Nested Interactive Array Language), $395/$995 Starwood Corporation PO Box 160849 San Antonio, TX 78280 512-496-8037 Microdyn: expert system shell, $300 Stochos 518-372-5426 M.1A: expert system shell, $2000 M1: expert system shell, $5000 KS-300: expert system shell Teknowledge Inc. 525 University Ave., #200 Palo Alto, CA 94301 415-327-6640 Arborist: decision support, $595 PC Scheme: AI language (Lisp), $95 Personal Consultant: expert system shell, $950 Personal Consultant Plus: expert system shell, $2950 Texas Instruments PO Box 80963, H-809 Dallas, TX 75380-9063 800-527-3500 Class Texpert Systems, Inc. 12607 Aste Houston, TX 77065 713-469-4068 TLC-Lisp: AI language (Lisp), $250 The Lisp Co. PO Box 487 Redwood Estates, CA 95044 408-426-9400 Lightyear: decision support, $495 The Management Advantage: decision support, $249 Trigger: decision support, $495 Thoughtware, Inc. Suite 1000a, 2699 S. Bayshore Dr. Coconut Grove, FL 33133 305-854-2318 PSL: AI language (Portable Standard Lisp), distribution costs ($75?) The Utah Symbolic Computation Group Department of Computer Science University of Utah Salt Lake City, UT 84112 -- -Paul S. R. Chisholm, UUCP {ihnp4,cbosgd,pegasus,mtgzz}!lznv!psc AT&T Mail !psrchisholm, Internet mtgzz!lznv!psc@topaz.rutgers.edu The above opinions may not be shared by any telecomm company. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jun 19 19:16:53 1986 Date: Thu, 19 Jun 86 19:16:48 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #153 Status: R AIList Digest Wednesday, 18 Jun 1986 Volume 4 : Issue 153 Today's Topics: Literature - AI and Organic Chemistry, AI Tools - Common Lisp on Silicon Graphics, Expert Systems - Conditional Independence References, Algorithms - Traveling Salesman Problem, Review - Spang Robinson Report Volume 2 No 6, Philosophy - Creativity and Analogy ---------------------------------------------------------------------- Date: Mon 16 Jun 86 13:24:13-PDT From: Matt Heffron Subject: Re: AI & Organic Chemistry A brand-new book from the American Chemical Society is: Artificial Intelligence Applications in Chemistry, Edited by: Thomas H. Pierce and Bruce A. Hohne ACS Symposium Series #306, published by ACS. 1986 28 chapters in 5 sections: Expert Systems, Computer Algebra, Handling Molecular Structures, Organic Synthesis, and Analytic Chemistry. Each chapter is a paper given at an ACS Symposium last September. -Matt Heffron BEC.HEFFRON@USC-ECL.ARPA ------------------------------ Date: Sun, 15 Jun 86 13:26:31 PDT From: Harry Weeks Subject: Common Lisp implementations. This note is in reply to a recent inquiry on this list for Common Lisp implementations on Silicon Graphics systems. Franz Inc. now supports our Extended Common Lisp, as well as Franz Lisp, on Silicon Graphics workstations. Both products incorporate an inter- face to the Iris graphic libraries. Extended Common Lisp is a complete and robust implementation of the Common Lisp language as specified in Guy Steele's book `Common Lisp: The Language.' We have added extensions that include a Symbolics-compatible Flavors system, a foreign-function interface, and extensive debugging tools. Franz Inc. also supports Extended Common Lisp on workstations available from ATT, ISI, Masscomp, Sun, and Tektronix. Inquiries are welcome and may be directed to our offices at 1141 Harbor Bay Parkway, Alameda, California 94501, (415) 769-5656, ...!ucbvax!franz!info. Harry Weeks Franz Incorporated ------------------------------ Date: 12 Jun 86 19:38:00 GMT From: pur-ee!uiucdcs!uicsl!bharat@ucbvax.berkeley.edu Subject: Re: Conditional independence in possibility theory I do not have the references you asked for. However if you are interested these are some other references I found useful relating to conditional independance and probabilities in EXPERT SYSTEMS. 1. Quinlan J.R. Inferno : a cautious approach to uncertain inference. The Computer journal, 26: 3, 255-269, 1983. 2. Allan P. White Predictor : An alternative approach to uncertain inference in Expert Systems. Proc - IJCAI 1985, Vol.1, 328-330, 1985. If you need them, please contact me at bharat@a.cs.uiuc.arpa, or write a note to net.ai Good luck R.Bharat Rao ------------------------------ Date: Sat, 14 Jun 86 15:22:01 pdt From: John B. Nagle Subject: Known solution to traveling salesman problem There is a well-known and fast method for finding near-optimum solutions to the traveling salesman problem. It was discovered at Bell Labs in the 1960s, and it is as follows: 1. Connect up all N points in some arbitrary order, resulting in a path with N-1 edges and two endpoints. 2. Pick two edges at random. Cut the path at these points. This produces three paths, each with two endpoints. 3. There are six possible ways to connect the paths into a single path. Try all six, and compute the total distance for each arrangement. Keep the arrangement with the shortest total length. 4. Iterate steps 2 and 3 until no improvement is observed for a reasonable number of iterations, at least N but less than N*N. I strongly suspect that the neural nets people have just rediscovered this classic algorithm, especially since the Business Week article mentions that the neural net approach produces near-optimal, not optimal, paths. Comparisons with the brute-force solution are misleading. John Nagle [While the Hopfield-net solution may well be based on similar mathematics, the flavor is quite different. It is more of a parallel "relaxation" process or fuzzy linking, with each node trying to link to neighbors in proportion to their nearness. Hopfield describes this as an analog process that cuts through the space of possibilities instead of moving around the outside as the iterative solutions do. The net quickly approaches a stable configuration of intersecting cliques (if that's not a contradiction) separated by longer paths, then the cliques fight it out to determine the final route. (The establishment of one clique disrupts others, so a slow gradient search for the optimum is necessary.) The lack of guaranteed optimality is primarily due to the initial rapid convergence -- it is possible to construct problems for which the true optimum is quite far from any broad "potential well" that would attract the system. Some algorithms use randomized "stochastic anealing" to get around this, others start the process many times from very different initial conditions, others just ignore the problem. For an interesting study of one such problem, see the Spring 1985 issue of Abacus. It presents a lengthy analysis of Lee Sallows' custom-built hardware for solving pangram puzzles by full search, then a short article by John Letaw showing how the same puzzles can (usually!) be solved by approximation/optimization on a microcomputer running BASIC. -- KIL] ------------------------------ Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.WISC.EDU Subject: Spang Robinson Report, Volume 2 No 6 Summary of Spang Robinson Report, Volume 2 NO. 6 June 1986 Emphasis on AI and Parallel Processing: There are 28 companies marketing parallel hardware with 900 machines installed for total revenues from 1985- mid 1986 of 160 million dollars. Alliant Computer Systems is working with Stanford and Lucid, Inc. in a DARPA funded project to develop a public domain LISP for parallel applications called QLISP. Control Data is working with the University of Georgia to develop a parallel Prolog and after that a parallel Lisp. Flexible Computer claims that 30 to 40 percent of its customers are interested in AI. Concurrent Lisp from Golden Common Lisp has been benchmarked on the Gabriel Triangle Benchmark at 86 percent of the speed of a Xerox 1108 Dandelion using one node of the IPSC hypercube. On a sixteen node hypercube, it runs at 9.1 times the speed. INTEL says that 25% of 1000 queries were oriented to AI. LISP Machine announced that it intends to have its Object LISP running on the INTEL hypercube by the end of May. Sequent Computer says that 10 to 15 percent of its customers based their decision buying decision on the availability of LISP, 50% were interested in AI. __________________________________________________________________________ Japan Watch: Arthur D. Little's Japan affiliate reported the results of a survey of twenty Japanese companies. The US has over a five year lead in Japan in AI but the gap will narrow with time. They predict the catchup will be completed by 1992. There is a twelve to one differential in the US favor in funds invested in AI up to 1985. The Japanese AI market in 1985 was 80 million while the American market was $412 million. Kansai Electric Power has been developing a diagnostic expert system for use with nuclear reactors with the prototype finished by March 1986. Kyushi Electric Power Company is field testing an expert system system for diagnosis and repair of electric power systems. Tokyo Electric Power Co., Inc., Hitachi Ltd and Mitsubishi Electric Corporation are working on expert systems for supply and demand for power and for planning system operations. Nippon Telephone and Telegraph will officially announce KBMS, an expert systems tool. NTT is negotiating with other companies for collaboration in the development of AI software. __________________________________________________________________________ AI at IBM: Dr. Herbert Schorr, Group Director for Products and Technology at IBM, stated that IBM does not plan to release a dedicated LISP machine or AI workstation. It considers its RT machine to be the IBM AI workstation. He claims that benchmarking at Carnegie Mellon has done benchmarking of this machine which shows it fares favorably with other AI languages and hardware. Most of IBM's efforts in developing expert systems are for internal applications and it does not see the need to compete with those already providing such products. There are 70 expert systems under development at IBM with 24 more to be added. ------------------------------ Date: Fri, 13 Jun 86 13:44:40 bst From: Gordon C Joly Subject: Re: Creativity and Analogy -- More Questions than Answers. Uttam Mukhopadhyay asks, in AIList Vol 4 #148 :- >Is there more to creativity than making interesting analogies? I am >inclined to believe that making interesting analogies is at the heart >of all intelligent activity that is described as creative. Hmmm... A friend described another friend as a potentially good novelist, because ``she always has a radically different view in the situation; she always has a new angle''. But is there analogy tucked away in her reasoning? And would we be able to elicit that knowledge from the `expert'? Finally, *is* creativity always intelligent, and in what sense of the word -- AI, machine intelligence or human intelligence? As for analogy, we always need hooks to hang ideas on, don't we? Gordon Joly INET: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk EARN: gcj%MATHS.QMC.AC.UK%CS.QMC.AC.UK@AC.UK UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Fri, 13 Jun 86 14:32:36 bst From: Gordon C Joly Subject: Re: Creativity and Analogy -- Coda. ``To the extent that a professor of music at a conservatoire can assist his students in becoming familiar with the patterns of harmony and rhythm, and with how they combine, it must be possible to assist students in becoming sensitive to patterns of reasoning and how they combine. The analogy is not far- fetched at all. -- Dijkstra.'' >From -- `Knowledge-Based Systems in Artificial Intelligence' by Randall Davis and Douglas B. Lenat, McGraw-Hill, 1982, page 163. Gordon Joly INET: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk EARN: gcj%MATHS.QMC.AC.UK%CS.QMC.AC.UK@AC.UK UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Mon, 16 Jun 86 10:41:48 edt From: Jay Weber Reply-to: jay@rochester.UUCP (Jay Weber) Subject: Re: Creativity and Analogy > At a recent talk in Ann Arbor, Roger Schank observed/implied that >a distinct characteristic of many creative people is the ability to >analogize. My understanding of analogizing is to define transformations >between two domains so that entities and relationships in one domain >can be mapped into corresponding entities and relationships in the >other domain. It appears that the greater the disparity in the "physics" >of the two domains, the higher is the creative effort demanded. > Not all transformations produce interesting results. Good analogies >must be interesting from the perspective of the particular creative >activity. True. Every pair of "things" is analogous in *some* sense, i.e. there exists a mapping between them. The utility of an analogy is how it leads one to use those things more successfully. > Is this model of creativity--making interesting analogies--valid >across the spectrum of creative actvities, from the hard sciences >(Physics, Chemistry, etc.) to the fine arts (painting, music)? >Is there more to creativity than making interesting analogies? I am >inclined to believe that making interesting analogies is at the heart >of all intelligent activity that is described as creative. I believe that one could give a reasonable definition of analogy that encompasses all intelligent activity, or at least inductive learning (which is a biggie as far as intelligence goes). I question, however, how useful it is in AI to relate a slippery word like "analogy" to an even slipperier word like "creativity". A formal approach with those two terms will satisfy very few people, and an informal approach will only give us an inflated opinion of the value of our own research, which is largely why people make such comparisons. Jay Weber Department of Computer Science University of Rochester jay@rochester.arpa ------------------------------ Date: Mon, 16 Jun 86 16:56:06 EDT From: "Col. G. L. Sicherman" Subject: Re: Creativity and Analogy This is a brief reply to U. Mukhopadhyay's article. > [...] > Is this model of creativity--making interesting analogies--valid > across the spectrum of creative actvities, from the hard sciences > (Physics, Chemistry, etc.) to the fine arts (painting, music)? > Is there more to creativity than making interesting analogies? I am > inclined to believe that making interesting analogies is at the heart > of all intelligent activity that is described as creative. "Creativity" is often idealized as the missing ingredient in computer consciousness, but what exactly does it mean? In most of the examples drawn from science, it means advantageously overriding the usual categories and compartments, since categorizing and compartmentalizing knowledge are characteristically scientific habits. Of course, making analogies is one way to achieve this. In art, creativity is much more straightforward! One creates a work of art where there was none before. The essence of this kind of creativity is to be able to perceive what _is not._ This follows in an essential way from the ability to perceive what one is taking for granted, in order to stop taking it for granted. A good reference is F. Perls et al., _Gestalt Therapy._ ------------------------------ Date: Tue 17 Jun 86 12:33:35-PDT From: Ken Laws Subject: Artistic Creativity From Col. Sicherman: "In art, creativity is much more straightforward! One creates a work of art where there was none before." While there is truth to this, I disagree with the implication that art, or certainly that >>all<< art, is pure creation. Most examples that I have seen are transformations. The artist sees a scene, technique, or concept that intrigues him, and searches for a way to capture the same thing in a new medium. This is analogy in a pure form, not the opposite of analogy. -- Ken Laws ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Mon Jun 23 06:48:07 1986 Date: Mon, 23 Jun 86 06:48:03 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #154 Status: R AIList Digest Monday, 23 Jun 1986 Volume 4 : Issue 154 Today's Topics: Seminars - Motion Planning (GMR) & Unifying Principles of Machine Learning (UPenn) & Parallel Execution of Logic Programs (UTexas) & Why Planning Isn't Rational (SRI) & Symbolic Representation of Waveforms (CMU) ---------------------------------------------------------------------- Date: Mon, 16 Jun 86 15:26 EST From: "Steven W. Holland" Subject: Seminar - Motion Planning (GMR) Seminar at General Motors Research Laboratories, Warren, Michigan (GMR): Motion Planning: a Survey of the State of the Art Joseph O'Rourke Department of Computer Science Johns Hopkins University Monday, June 23, 1986 Abstract Motion planning from the viewpoint of computational geometry is the problem of moving an object (a robot hand, for example) from an initial to a final position in the presence of fixed obstacles. A large number of algorithms have been developed for various cases of this problem recently. I will describe the two main paradigms for solving this problem, growing algorithms and Voronoi diagram algorithms, and survey the known results. Several special cases will be discussed, including moving a disk, moving a ladder, moving through a door, and moving around a corner. I will also touch on the more complex problem of moving through an environment which is not itself fixed, for example, one that contains several independently moving robots. Joseph O'Rourke has been Assistant Professor at Johns Hopkins University since receiving the Ph.D. degree in Computer Science at the University of Pennsylvania in 1980. His dissertation research was in computer vision, and he has published in pattern recognition, but now his research is focused on computational geometry. O'Rourke is a NSF Presidential Young Investigator. -Steve Holland, Computer Science Department ------------------------------ Date: Wed, 18 Jun 86 11:08 EDT From: Tim Finin Subject: Seminar - Unifying Principles of Machine Learning (UPenn) CIS Colloquium 3 p.m. Thursday, June 19, 1986 216 Moore School, University of Pennsylvania MACHINE LEARNING: UNIFYING PRINCIPLES AND RECENT PROGRESS Ryszard S. Michalski University of Illinois Machine learning, a field concerned with developing computational theories of learning and constructing learning machines, is now one of the most active research areas in artificial intelligence. An inference-based theory of learning will be presented that unifies the basic learning strategies. Special attention will be given to inductive learning strategies, which include learning from examples and learning from observations and discovery. We will show that inductive learning can be reviewed as a goal-oriented and resource-constrained inference process. This process draws upon the learner's background knowledge, and involves a novel type of inference rules, called inductive inference rules. In contrast with truth-preserving deductive rules, inductive rules are falsity-preserving. Several projects conducted at our AI Laboratory at Illinois will be briefly reviewed, and illustrated by examples from implemented programs. ------------------------------ Date: 19 Jun 86 17:14:14 GMT From: ucbcad!nike!lll-crg!seismo!ut-sally!leung@ucbvax.berkeley.edu (Clement Leung) Subject: Seminar - Parallel Execution of Logic Programs (UTexas) AN ABSTRACT MACHINE BASED EXECUTION MODEL FOR COMPUTER ARCHITECTURE DESIGN AND EFFICIENT IMPLEMENTATION OF LOGIC PROGRAMS IN PARALLEL Manuel V. Hermenegildo Dissertation Defense The University of Texas at Austin Department of Electrical and Computer Engineering June 20, 1986 - 11:00 am - ENS431 Parallel execution represents one way in which the execution speed of logic programs can be increased beyond the limits of conventional systems. However, most proposed parallel logic programming systems lack the optimizations and storage efficiency of high-performance sequential implementations. A parallel execution model for logic programs will be presented which is based on extending to a parallel environment the techniques introduced by the "Warren Abstract Machine", which have already made very fast and space efficient sequential systems a reality. Therefore, the model is capable of retaining sequential execution speed similar to that of current high performance systems, while extracting additional gains by efficiently supporting parallel execution. The model is described down to the Abstract Machine level, specifying data areas, operation, and a suitable instruction set. Several techniques are introduced which offer efficient solutions to areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the specification of control and management of the execution tree, the detection and handling of variable binding conflicts in AND-Parallelism, support for "don't know" non-determinism and treatment of distributed backtracking, goal scheduling and memory management issues etc. These claims are supported by simulations. ------------------------------ Date: Thu 19 Jun 86 17:22:52-PDT From: Amy Lansky Subject: Seminar - Why Planning Isn't Rational (SRI) WHY PLANNING ISN'T RATIONAL Terry Winograd (TW@SAIL) Stanford University (Computer Science, Linguistics, and CSLI) 11:00 AM, MONDAY, June 23 SRI International, Building E, Room EK242 (note room change) Orthodox AI approaches to describing and achieving intelligent action are based on a "rationalistic" tradition in which the focus is on a process of deducing (using a representation of some kind) the consequences of specific acts (operations) and searching for a sequence of acts that will lead to a desired result (goal). This works reasonably well for some limited domains, but falls far short of being a general theory of intelligent action. It does not work well in the small (how I operate my finger muscles, or where an amoeba slithers), or in the large (how I conduct my life or where my research is headed). Even in the cases of clearly explicit rational planning (e.g. planning a bank robbery), the relation between plan and execution is not easy to capture (what happens when the teller sneezes?). In a recent book written jointly with Fernando Flores, I have proposed a different basis for looking at action and cognition, focussing on the "thrownness" of action without reflection, and on the open-endedness of interpretation. Any alternative such as ours must address several obvious questions: Why is the naive view of rational decision-making and action so intuitively plausible if it isn't right? How can we account for the evolution of complex behavior which is effective in an environment? What implications does it have for AI and the design of computer systems in general? I will address these questions and related others, focussing on some different issues from those raised in my talk to CSLI a couple of weeks ago on "Why language isn't information". VISITORS: Please arrive 5 minutes early so that you can be escorted up from the E-building receptionist's desk. Thanks! ------------------------------ Date: 18 Jun 86 18:59:25 EDT From: Dave.McKeown@maps.cs.cmu.edu Subject: Seminar - Symbolic Representation of Waveforms (CMU) Monday June 23 1:30pm 5409 Wean Hall A Symbolic Representation of Waveforms Using Multi-Resolution Analysis Dr. Aviad Zlotnick Department of Mathematics and Computer Science Hebrew University, Israel A multi-resolution technique for ``qualitative'' analysis of waveforms was suggested by Witkin in 1983, and has since been studied extensively, both in theory and in practice. In the first part of the talk we reconsider Witkin's definition of qualitativity and outline a few weaknesses of his method. In the second part we describe a representation based on an alternative definition of qualitativity. We show that our method results in waveform descriptions which are nearer to human intuition, are easier to compute and can incorporate more domain knowledge. Furthermore, a symbolic (verbal) description of waveforms derived from this representation is shown to capture the waveforms' essential visual properties. If you'd like to talk with Aviad while he is here on the 23rd, please send mail to Dave McKeown@a. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Mon Jun 23 06:48:22 1986 Date: Mon, 23 Jun 86 06:48:19 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #155 Status: R AIList Digest Monday, 23 Jun 1986 Volume 4 : Issue 155 Today's Topics: Queries - AI Tools Survey & Financial Expert Systems Survey & Recognition Software & HYDRO & ES Shell & Stereo Vision, Expert Systems - Validation and Verification, Resources - Common Lisp Discussion List Philosophy - Metaphilosophy and Computer Ethics, Psychology - Doing AI Backwards ---------------------------------------------------------------------- Date: Tue, 17 Jun 86 19:23:19 PDT From: heher%ford-scf1.arpa@ford-scf1.arpa (Dennis Heher) Subject: Request for AI Tools Survey I heard that there is an unclassified report available that compares all of the commercial AI tools (KEE, Knowledge Craft, ART, etc.). This report was supposed to have been generated at/for Wright-Patterson Air Force Base. Does anyone have any information (title, report number, where I can obtain a copy) on such a report? Thanks, Dennis Heher heher@ford-scf1.arpa Ford Aerospace & communications Corporation 1260 Crossman Avenue Sunnyvale, California 94089 (408) 743-3944 ------------------------------ Date: 16 Jun 86 16:30:00 GMT From: pur-ee!uiucdcs!convex!ti-csl!dbdavis@ucbvax.berkeley.edu Subject: Financial Expert systems survey I'm looking for a list of systems/software houses that are active in the development and/or marketing of financial expert systems. I'd also be curious to know what ( if anything ) the major insurance companies are up to in terms of in-house development of expert systems - which companies, and what applications ( risk assessment, etc. ). Any help is greatly appreciated. The info will be used as part of a market survey I'm doing for a class. --db davis ------------------------------ Date: 19 Jun 86 15:18:21 GMT From: ihnp4!iwvae!gph@ucbvax.berkeley.edu (haberl) Subject: AI routines This is my first time posting to the net. I am doing some research on Artifical Intellegence processes (Voice Recognition, Text Recognition and Hand Writing Recognition). If any of you AI wizards can provide me a reference, on where I can find some routine to provide these services it would be much appreciated. The references I need are either Information on Public Domain software or Information on companies that sell software like this. THANXS....... Gregory P. Haberl (312) 979-7072 or (303) 691-4993 Technocrats, Inc. Po Box 2238 Don't Yet Pathway for return Littleton, Co 80161 ------------------------------ Date: Thu, 19 Jun 86 10:33:30 bst From: Gordon Joly Subject: HYDRO Does anyone have any information on the HYDRO system, a water resources management expert system? Many thanks in advance, Gordon INET: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk EARN: gcj%UK.AC.QMC.MATHS%UK.AC.QMC.CS@AC.UK UUCP: ...!seismo!ukc!qmc-ori!gcj [I'll send Gordon the reference to John Reiter's SRI work that was included in AIList V4 #141, June 18. -- KIL] ------------------------------ Date: Fri, 20 Jun 86 07:20 CDT From: Araman@HI-MULTICS.ARPA Subject: Expert System shell needed for thesis: I'm doing a Master's thesis concerning combining an expert system shell and a DBMS. To do this, I need to work with modifying some shell. If anyone out there has a small, frame or rule based expert system shell written in LISP or C, and you're willing to give away a copy in the name of furthering science, send a message to: ARAMAN -at HI-MULTICS.ARPA Thanks a lot! Sam Levine ------------------------------ Date: Fri, 20 Jun 86 08:11:53 mdt From: crs%f@LANL.ARPA (Charlie Sorsby) Subject: Vision Request I am getting started on a Master's Thesis in the general area of Computer Vision. Since [...] vision and AI appear to overlap considerably, I'm trying AIList. I apologize if this is not an appropriate medium for the following request. I would sincerely appreciate any pointers to literature and current research in this area and particularly in the area of stereo vision. I have Computer Vision by Ballard & Brown, the vision section of the Handbook of AI, Image Understanding 1984, Ullman & Richards, eds. and a few papers that I've found. What are the current hot research areas in this field? What, in your opinion, are the most important problems to be solved? What, aside from stereopsis and range-finding are options for depth-information recovery? What, currently, appears to be the best method of obtaining this information fast enough to be useful? Is any research being directed at the possibility of real- time stereo vision? What are your opinions of its feasibil- ity? Its value? If any of you have papers that you would be willing to share, my mailing address is: Charlie Sorsby Los Alamos National Laboratory Post Office Box 1663 MS-J957 Los Alamos, NM 87545 Opinions are welcome and please also mention if I may quote you or if you prefer that I don't. I would also welcome suggestions for other lists where it may make sense to make this request. [Vision-List@ADS is known. --KIL] While I try to follow the network as time permits, I would appreciate it if you could mail information to me by way of one of the paths in my signature. I will happily summarize any information that I receive and post it to AIList. Charlie Sorsby ...{cmcl2, ihnp4, ..}!lanl!crs crs@lanl.arpa [I generally forward vision items to Vision-List (and did this time), but am permitting this message as a favor to Charlie. AI-related discussion of vision (e.g., for autonomous navigation) is pertinent to this list, but discussion of particular algorithms would generally not be. -- KIL] ------------------------------ Date: Fri, 20 Jun 86 14:17 PDT From: Tom Garvey Subject: Re: Expert System Validation and Verification I think the notion of V&V for expert systems highlights a number of points about the field. First, in the words of David Mizell (formerly of ONR), "AI is being overbought." People that should know better are taking an attitude that there are sufficient useful AI systems out there that we should be concerned with formal notions of their capabilities. In point of fact, AI is very much a research topic (I almost said science), and for most problems we are struggling to find any solution at all, much less one that will be operationally useful and verifiable. The traditional rationale for attempting an "AI" solution to a problem is that we don't know how to solve the problem directly (if we did, why screw around), or that our problems come from a large class of ill-specified problems where flexibility in the problem-solving approach is of paramount importance (otherwise, ...). AI approaches typically involve non-deterministic processes such as context-sensitive search (frequently in large, ill-structured knowledge-bases), and their performance is therefore extremely difficult to describe much less quantify. (We don't do a very good job of V&V on deterministic systems yet.) Even statistical validation (i.e., try a million random test cases and measure resulting performance) will be questionable, as characterizing an appropriate set of test cases spanning the range of possible or likely inputs will be extremely difficult. At this point, I view most expert system development as not much more than programming in a new language. The language offers ease of specification and representation of certain types of information (oops, knowledge), but does not lend itself well to either V&V, maintenance, or robust operation. To the extent that we use expert system developments to help understand and structure problems, these shortcomings are not too significant; to the extent that we view the systems as the solutions themselves, the shortcomings are significant. All this doesn't help your quest much, but perhaps it will help lower your expectations. Cheers, Tom ------------------------------ Date: Sun, 22 Jun 86 15:05 EDT From: Brad Miller Subject: Lisp Discussion List Unfortunately there are few relevant discussion lists on the Arpanet side of the gateway. We do have one on workstations and others on particular micros or Lisps, but nothing of the required generality. ... -- KIL [...] Note that there IS a common-lisp mailing list , though it is for language definition purposes. Brad Miller University of Rochester miller@rochester.arpa ------------------------------ Date: Mon, 16 Jun 86 16:06:29 EDT From: "Col. G. L. Sicherman" Subject: Re: Computer Ethics (from Risks Digest) I have a few comments on _Metaphilosophy,_ as summarized by Bruce Sesnovich: > The introductory article, James H. Moor's "What is Computer Ethics," is > an ambitious attempt to define Computer Ethics, and to explain its > importance. According to Moor, the development and proliferation of > computers can rightly be termed "revolutionary": "The revolutionary > feature of computers is their logical malleability. Logical > malleability assures the enormous application of computer technology." > Moor goes on to assert that the Computer Revolution, like the > Industrial Revolution, will transform "many of our human activities and > social institutions," and will "leave us with policy and conceptual > vacuums about how to use computer technology." "Logical malleability" sounds vague to me. If it's just an abstract phrase for programmability, then I think Moor neglects the real signi- ficance of computers: that (unlike machines) they accept differing input, and produce differing output. I agree fully that computers will cause revolutions. But this talk of "conceptual vacuums" is born of unavoidable myopia. None of our present- day prognosticators have shown any serious understanding of the future, except a few science-fiction writers whom nobody takes seriously. I suggest that posterity will regard _us_ as the "vacuum" generation, of an age "when nobody knew how to use computer technology." > An important danger inherent in computers is what Moor calls "the > invisibility factor." In his own words: "One may be quite > knowledgeable about the inputs and outputs of a computer and only dimly > aware of the internal processing." These hidden internal operations can > be intentionally employed for unethical purposes; what Moor calls > "Invisible abuse," or can contain "Invisible programming values": > value judgments of the programmer that reside, insidious and unseen, in > the program. Here Moor appears to be about 30 years behind McLuhan. Try this: "One may be quite knowledgeable about reading and writing and only dimly aware of the details of book production and distribution." Or this: "One may be quite knowledgeable about watching TV and only dimly aware of the physics of broadcasting." Isn't it rather naive to think that the hidden values of the computer medium lie in if-tests and do-loops? To quote one of McLuhan's defocussed analogies: "You must talk to the medium, not to the programmer. To talk to the programmer is like complaining to the hot-dog vendor about how badly your team is playing." Col. G. L. Sicherman UU: ...{rocksvax|decvax}!sunybcs!colonel CS: colonel@buffalo-cs BI: csdsicher@sunyabva ------------------------------ Date: 15 Jun 86 09:08:28 GMT From: ernie.Berkeley.EDU!tedrick@ucbvax.berkeley.edu (Tom Tedrick) Subject: Doing AI Backwards (continued) More on "Doing AI Backwards" (I can't bear to do anything in a normal way :-) The exact, concrete nature of models of computation allow a certain clarity to exist, which was not easily experienced previously. Hence, when these models apply to other fields, we may find a new clarity that was previously lacking. For example, studying computational complexity has made it clear that memory can be an expensive resource, and efficient use of memory of great importance. Now, can we use this insight to better understand certain phenomena outside the field of computational devices? I suggest that memory is also a scarce resource when we take the human mind as our object of study. Example: Suppose I am asked to pick up a carton of milk at the grocery store after work. For some reason this kind of request irritated me for years, yet I could not quite pin down the reason for my irritation. I did not mind walking to the store, spending the money, etc. It turns out that what bothers me is the use of my memory to store the request. Thus for the rest of the day I have less space in my short term memory for thinking about research, etc. All my work was made less productive by this misuse of space in memory. Hence the individual who asks such seemingly small favors may be really imposing a heavy cost on his victim. From a catastrophe theory point of view, we might also suggest the danger of less efficient thinking due to reduced space available in memory being magnified into some larger catastrophe. Another thing that is clear from studying computational complexity is that certain problems take more computing time than others. What insight can we gain about the behavior of the human mind from this simple idea? Well, suppose someone asks you a question, expecting a simple yes or no answer. (Supposedly the truth is simple, so why should you need to think about the question?) But suppose you have greater insight into subtle problems posed by the question than the questioner does. But you need time to think about it. (By knowing about computational complexity, you wisely realize that your brain needs to use a few cycles to figure out what to say.) Some possibilities: (1). You answer immediately anyway, yes or no. Then later one of the subtleties may come back to haunt you, as the (dumb) questioner comes back to you saying "Well you said yes, now you are trying to squirm out of it, you no good scum." Or, "You were not honest with me, you devious jerk", when you are unable to live up to your word. (2). You think for awhile. Then the questioner may think "Boy is this guy dumb. Can't even answer a simple question." Or, "This guy is trying to come up with some kind of a line so as to pull a fast one on me." Or he may say, "ANSWER THE QUESTION! YES OR NO!" if he is on a power trip, like, say, a Senate Investigator. In any case, asking questions and expecting an immediate response, saying "If you were honest you would not hesitate to answer" is clearly unfair. OK, now you can start flaming. But please, for a change, attack what I said instead of sending hate mail attacking me as an individual. I have no interest in receiving hate mail. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Wed Jun 25 06:54:10 1986 Date: Wed, 25 Jun 86 06:54:05 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #156 Status: R AIList Digest Wednesday, 25 Jun 1986 Volume 4 : Issue 156 Today's Topics: Queries - Expert System Applications Products & Graph Drawing Program & Image Analysis Expert System, Expert Systems - Image Analysis & Financial Expert Systems, Representation - Function and Form, Philosophy - Creativity and Analogy ---------------------------------------------------------------------- Date: Tue 24 Jun 86 12:42:41-PDT From: Matt Heffron Subject: Query: Expert System Applications Products As one of the developers of Beckman Instruments' SpinPro (TM) expert system, I am interested in finding out about any other Expert System Applications (NOT shells) which are actual, delivered products (especially any which run on PCs). I'm more interested in those which are marketed openly, rather than custom projects for a single customer. Reply directly to me and I will post a summary of replies. Thanks, Matt Heffron BEC.HEFFRON@USC-ECL.ARPA SpinPro (TM) is a trademark of Beckman Instruments, Inc. ------------------------------ Date: Tue, 24 Jun 86 21:57:06 PDT From: larus@kim.berkeley.edu (James Larus) Subject: Wanted: Graph Drawing Program I need a program to display directed, cyclic graphs on a Symbolics 3600. Does anyone have such a program that I could use? Either the program or rumors of such a program would be appreciated. /Jim ------------------------------ Date: 24 Jun 86 16:09:51 GMT From: ucdavis!deneb!524789610rmd@ucbvax.berkeley.edu (524789610rmd) Subject: Image Analysis Expert System We are trying to develop an expert system for the recognition of white blood cells and have a need for a suitable inference engine. We have considered using EMYCIN, however, it is difficult to get and we are not sure it will work correctly with our system. Basically, we will be using conventional image analysis techniques to extract points in feature space from a cell and then use the inference engine to decide what type of cell it is (as opposed to statistical methods). Does anyone out there have any ideas about what type of inference engine we should use? BTW, we are developing the system on a uVAX II using VAX Common Lisp. Thanks in advance! - Mark Nagel ...{ucbvax,lll-crg,dual}!ucdavis!524789610rmd UUCP ^ | will be "donovan" after 6/30/86 ------------------------------ Date: Tue 24 Jun 86 22:57:38-PDT From: Ken Laws Reply-to: AIList-Request@SRI-AI.ARPA Subject: Image Analysis Expert System I doubt that it makes much difference what inference engine Mark Nagel uses for his vision problem, as long as it allows calls to external routines. Since almost the entire vision problem must be handled by procedural attachment ("conventional image analysis techniques"), the inference engine need only provide the capabilities of a simple programming language. A probabilistic or fuzzy-reasoning system such as Prospector might have considerable advantage over logic-based approaches, but would have much the same flavor as the statistical techniques that Mark wishes to avoid. The real problems in visual pattern recognition are in computing robust descriptors (esp. if they must be computed quickly) and in the knowledge-representation (i.e., knowing what kind of descriptors to compute and how to store the answers). Very little of the problem has to do with logical reasoning, forward or backward chaining, etc. -- Ken Laws ------------------------------ Date: Tue, 24 Jun 86 9:23:16 CDT From: Glenn Veach Subject: Re: Financial Expert Systems Glenn Shafer (of the Dempster-Shafer fame) has been developing systems for both financial and management support, I am not sure about marketing. You can reach him at: Glenn Shafer 313 C Summerfield Hall School of Business University of Kansas Lawrence, KS 66045 (913) 864-3117 ------------------------------ Date: Thu 19 Jun 86 22:18:34-PDT From: Ken Laws Subject: Function and Form Those who responded to my query on shape may enjoy reading John Hopcroft's "The Impact of Robotics on Computer Science" in the June issue of Communications of the ACM (pp. 486-498). The article covers quadratic shape modeling and the need for topology and related mathematics in modeling and motion planning. Marc Raibert's following article on legged robots is also interesting. There is a great deal of "function" that must be derived from dynamics rather than shape. -- Ken Laws ------------------------------ Date: Wed 18 Jun 86 10:39:46-PDT From: Pat Hayes Subject: Artistic Creativity Of course art isnt 'pure creation' ( whatever THAT might mean ). Read Kenneth Clarke "the Nude", or any decent piece of historical criticism. Most artists dont even use a new medium, which is just as well or we would have run out of media long ago. After reading Jay Webers complaint about space in AIList being wasted on LISP, let me back him up by suggesting that space not also be wasted on sub-undergraduate amateur pseudo-philosophy. Severely editing anything from Gordon Joly might be a good way to start. Pat Hayes [The current policy, of course, is to screen on the basis of content rather than source. -- KIL] ------------------------------ Date: Thu, 19 Jun 86 12:41:01 est From: munnari!trlamct.oz!andrew@seismo.CSS.GOV (Andrew Jennings) Subject: Re : creativity and analogy (Andrew Jennings@ Telecom Research,Aus) Sure, many creative people are good at drawing analogies : but is that the source of their creativity ? I would argue that it is more their ability to hold two seemingly disparate situations in consideration simultaneously : if as part of this an analogy drops out then fine, but is an analogy creative ? In one sense it is almost deductive, I think. For me Koestler's view of the processrings more true. In this view all creative acts are the result of simultaneous consideration of seemingly completely disparate situations : producing something completely new as a result, but not by reasoning by analogy. Also here Minsky's view that we put creativity on too high a pedestal is relevant. Why do we ? Because we have a vested interest in this position ? Perhaps. Are we simply afraid of pursuing what creativity is ? So what IS creativity ? ------------------------------ Date: Wed, 18 Jun 86 23:23:58 PDT From: larry@Jpl-VLSI.ARPA Subject: Creativity (When you read "hir" pronounce it as if you meant to say "him" and halfway through decided to say "her." It becomes "hi-er," a diphthong hard to distinguish from "hear.") I'm an artist in three media (four if you count programming, which I do). To me creativity is just another skill which I use without giving it much thought, at least until discussions like these come along. Here are some of my ideas on the subject. Creation is a recombination process. When I come up with a new character for a story, parts of hir come from prior percepts: a complexion from him, a walk from her, an accent from yet a third person. (Or a slant from this letter, a squiggle from that number, etc., if I'm painting!) Recombination done randomly is not very fruitful. Creativity includes ways to cut down on the number of recombinants. Or possibly A way, because this winnowing is done subconsciously. I don't know consciously what it/they are, but I FEEL them working, so I know they/it exist. The first step in creativity is "playing," "fingering" the contents of the field within which a solution is desired. This apparently random, frivolous activity is anything but. It provides some of the pleasure which fuels an artist, and it transfers the elements of the field out of short- term memory into long-term memory (making them easily accessible). Or it may place them into some kind of mid-term memory, or load the memories with some kind of potential which makes these elements of long- term memory more likely to be accessed than others, thereby decreasing the number of combinations produced. The second step introduces more (obviously) purposeful activity. The artist begins looking for the solution to a problem. It's important that she (pronounced she, just as if it weren't spelled s/he, which it isn't) not begin with a goal, or at least not one that's narrowly and urgently defined. You don't want hir to overly restrict hir search for useful neologs. (Linguists, help! There has to be a better word than neolog.) This is a less-pleasurable activity than the playing stage, more logical and conscious. Like the first stage, it transfers percepts/concepts to long-term memory and reinforces them. And it "grinds in" to hir mind the goal of the problem-solving, so well that even in the next stage some part of hir is seeking it. The third stage is relaxation, where the conscious mind transfers its attention to some other activity, one which holds just enough attention to prevent hir from falling into deep sleep (light sleep is OK). But not so engrossing that she begins solving another problem, which would interfere with the current problem. Routine physical activities seem to be best. Ironically, this "idleness" is the most crucial and productive phase. Because at some point she will experience the "Eureka" phenomenon, where a combination of percepts/concepts matches the mask of the goal and slips through into consciousness. (Just before the match occurs she may get a "Something's happening!" feeling that will wake hir up from hir doze/daydream/dawdling/drudgery.) This is the magical moment, where (it feels as if) another spirit, a genie/genius pushes the solution into hir consciousness. There's usually surprise because the neolog is strange ("Did that REALLY come from me?!") and delight because it solves the problem so well. Or at least it seems to. Now comes stage four: fleshing out what is often a skeletal though pivotal part of the solution. After that is stage five: evaluating the solution. Then comes the last stage: making the solution operational. The evaluation stage is in some ways the least pleasant for the artist (or engineer/scientist/whatever), but in fact most creativity is faulty and must be rejected--but not forgotten; some of the worst ideas have the seeds of wonder in them. The effective artist learns not to be afraid of the bizarre, ugly, taboo, incorrect productions, but to delight in them and use them. (And to delight in the ordinary and plain and learn to see them as equally strange and wonderful.) So, in answer to the original question: Yes, analogy is essential to creativity, but I would prefer to make a more general statement. The core of creativity is a process of combining and recombining percepts and concepts, guided and limited by a channeling process, and the matching of each combination against a template, most of it done at a sub- or semi- conscious level. And with that definition we can design a creative computer. Larry @ jpl-vlsi.ARPA ------------------------------ Date: Thu, 19 Jun 86 19:52 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Creativity and Analogy Gordon C Joly asks: > A friend described another friend as a potentially good novelist, >because ``she always has a radically different view in the situation; >she always has a new angle''. But is there analogy tucked away in her >reasoning? ... The description suggests a person who makes interesting analyses (or abstractions) of situations, i.e. she "understands" situations in terms of unusual world models. While this quality, by itself, might enable her to make good commentaries and write fine essays, there must be something more to make her a good novelist: the ability to find an expression for (instantiate) this world model in the medium of language. To abstract and then instantiate is but one way to make transformations (analogies) between domains. Uttam Mukhopadhyay GM Research Labs ------------------------------ Date: Thu, 19 Jun 86 19:54 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Creativity and Analogy Jay Weber states: >I believe that one could give a reasonable definition of analogy that >encompasses all intelligent activity, or at least inductive learning >(which is a biggie as far as intelligence goes). I think inductive learning is only half of the story. The other half is to instantiate what is learned, in another domain. >I question, however, >how useful it is in AI to relate a slippery word like "analogy" to an >even slipperier word like "creativity". A formal approach with those >two terms will satisfy very few people, and an informal approach will >only give us an inflated opinion of the value of our own research, >which is largely why people make such comparisons. Yes, I do want to understand "creativity" in terms of less slippery concepts, such as "analogy". We are forced to start with informal approaches but hope to find more formal definitions. I do not understand why a formal approach would satisfy very few people or why an informal approach would serve no useful purpose. I am sure that you do not imply that an analysis (formal or informal) of >anything< is futile. What is it about "creativity" that makes its analysis a no-win proposition? Uttam Mukhopadhyay GM Research Labs ------------------------------ Date: Fri, 20 Jun 86 18:47:57 bst From: Gordon Joly Subject: Creativity, Analogy, Art and Humanity. > "In art, creativity is much more straightforward! One creates a > work of art where there was none before." Col. Sicherman. Indeed! Look for the art in the performance of ``My Way'' by Sid Vicious. And what of humour? This takes analogy and turns it on it's head. And this digest has noted in the past that humour is a key activity of the human intellect, which serves to distinguish it from the mere machine intellect of myself and others like me. The Joka. Disclaimer -- These opinions are not those of my programmer, or the operating system in which I reside. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Wed Jun 25 06:54:21 1986 Date: Wed, 25 Jun 86 06:54:16 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #157 Status: R AIList Digest Wednesday, 25 Jun 1986 Volume 4 : Issue 157 Today's Topics: Discussion Lists - The Structure of AI, Knowledge Science, and 6th-Generation Computing, Theory - Parallelism ---------------------------------------------------------------------- Date: Thu, 19 Jun 86 11:48:46 edt From: Tom Scott Subject: Ken's Plea for Help!!!! The moderator of the AI-List has made an impassioned plea for help. I would like to help, but before I offer to start a new Arpanet, Csnet, or UUCP newsgroup, I'd like to put forth an organization to Ken's list of possible new newsgroups. This organization comes from the Japanese side of the Pacific, and is outlined by Brian Gaines in a recent article, "Sixth Generation Computing: A Conspectus of the Japanese Proposals" ("SIGART Newsletter", January 1986, pp. 39-44). Figure 1 of the article, complemented by the fundamental topics that I've added for the sake of completeness, cuts the cake thusly: Theoria | Praxis | Techne ------------ | -------------------- | -------------------- | Expert systems | Pattern recognition Physiology | | Cognition | Machine translation | Learning Psychology | systems | Problem solving | | Natural language Linguistics | Intelligent CAD/CAM | Image processing | systems | Speech recognition Logic | | Man-Machine interface | Intelligent robotics | ============================================================= | Managerial | Expert systems Epistemology | cybernetics | | Decision support | Development languages Modern logical| systems | and environments metaphysics | Information | | retrieval systems | Computing/knowledge Vedic Science | | machines ============================================================= THE UNIFIED FIELD OF ALL POSSIBILITIES This is the world of the sixth generation: knowledge science and knowledge systems. The fifth generation, which deals mainly with the daily realities of knowledge engineering and expert systems, as well as with the advanced research and development of VLSI architectures for the processing of Prolog code and database systems, is distinct from the sixth generation. To get a better feel for these distinctions, I'd like to suggest the following homework assignment for new newsgroup moderators: (1) Read Brian's article. (2) Read the abstract of the paper that I'll be presenting to the sixth-generation session at the 1986 International Conference on Systems, Man, and Cybernetics (Atlanta, October 14-17); the abstract is appended to this message. (3) Think before you flame; then write back to me or to this newsgroup and share your thoughts. We are children of the cybernetic revolution and we are witnessing the rising sunshine of the Age of Enlightenment. Tom Scott CSNET: scott@bgsu Dept. of Math. & Stat. ARPANET: scott%bgsu@csnet-relay Bowling Green State Univ. UUCP: cbosgd!osu-eddie!bgsuvax!scott Bowling Green OH 43403-0221 ATT: 419-372-2636 * * * Abstract of the sixth-generation SMC paper * * * KNOWLEDGE SCIENCE The Evolution From Fifth-Generation Expert Systems To Sixth-Generation Knowledge Systems Theory, practice, technology--these are the makings of a full vision of knowledge science and sixth-generation knowledge systems. Prior to the establishment of research and development projects on the Fifth Generation Computing System (FGCS), knowledge science did not exist independent of knowledge engineering, and was conceptualized only in technological terms, namely, expert systems and "machine architectures for knowledge-based systems based on high-speed Prolog and relational database machines" (Gaines 1986). Although the design and development of fifth-generation machines and expert systems will continue for years to come, we want to know now what can be done with these ultra-fast architectures and expert systems. What kinds of knowledge, other than the knowledge of domain experts in fifth-generation expert systems, can be acquired and encoded into sixth-generation knowledge systems? What can be done on top of fifth-generation technology? How can fifth-generation architectures and expert-system techniques be extended to build intelligent sixth-generation knowledge systems? Beyond the fifth generation it is necessary to envision practical applications and theoretical foundations for knowledge science in addition to the technological implementation of machine architectures and expert systems. This paper discusses the full three-part vision of knowledge science (theoria, praxis, and techne) that is emerging around the world and has been treated by the Japanese under the title Sixth Generation Computing System (SGCS). Theoria: As indicated in Brian Gaines's article, "Sixth Generation Computing: A Conspectus of the Japanese Proposals" ("ACM-SIGART Newsletter" January 1986), the theoretical foundations of knowledge science are arranged in levels, proceeding downward from physiology to psychology to linguistics to logic. Continuing in this direction toward deeper foundations, the field of knowledge science embraces epistemology and modern logical metpahysics. On the empirical side of the deep foundations is the probability-based epistemology of pragmatism, explicated in Isaac Levi's "The Enterprise of Knowledge" (1980); on the transcendental side are Immanuel Kant's "Critique of Pure Reason" (1781-87) and Edmund Husserl's "Formal and Transcendental Logic" (1929). A simplified diagram of the four main divisions of mind, based on one sentence of the Critique ("Beide sind entweder rein, oder empirisch": B74), is: Understanding Sensibility | E Knowledge Images m of --------> Objects p objects | | ----------------------+----------------------- T | r Pure concepts Schemas Pure forms of a (categories) --------> intuition n and principles | (space and time) s | Praxis: The SGCS project is also concerned with the practical applications of knowledge science. These applications are organized under four headings: expert systems, machine-translation systems, intelligent CAD/CAM, and intelligent robotics. Another way of organizing the applications of knowledge science in terms familiar to the IEEE Systems, Man, and Cybernetics Society is: managerial cybernetics, organizational analysis, decision support, and information retrieval. Stafford Beer's "The Heart of Enterprise" (1979) is the focal point of our discussion of knowledge-science praxis. Techne: The SGCS project targets eight technological areas as the basis for the future research and development of sixth-generation knowledge systems: pattern recognition, cognition, learning, problem solving, natural language, image processing, speech recognition, and man-machine interfacing. To fully realize the R&D potential of these eight areas, sixth-generation knowledge scientists must be on friendly terms with the following areas of expertise from fifth-generation knowledge engineering: (1) Expert systems. (a) Concepts and techniques for the acquisition, representation, and use of knowledge. (b) The software engineering of knowledge systems, including a methodology for the building of expert systems and the management of expert-system development teams. (c) Expert systems and shells. (2) Three levels of systems and software. (a) Production systems (e.g., ITP, Prolog, and OPS83). (b) Traditional AI/KE languages (e.g., Lisp and Prolog). (c) Development environments and utilities (e.g., Unix, C, and Emacs). (3) The knowledge engineer's technical intuition of a computational knowledge machine. (a) Lambda Consciousness, based on the idea of a Lisp machine. (b) Relational database machines. (c) Prolog machines. The paper includes observations from the experience of the University of Wisconsin-Green Bay in its attempts to establish a regional knowledge-engineering and knowledge-science resource center in the Northeastern Wisconsin area. * * * Finis * * * ------------------------------ Date: 19 Jun 1986 2240-PDT (Thursday) From: Eugene miya Subject: Fed up with all this `talk' about parallelism The following are some ideas I have been thinking about with the help of one co-worker. I plan to post this to several groups where I regard parallelism discussions are significant such as parsym, ailist, and net.arch. The ideas are still in formation. >From the Rock of Ages Home for Retired Hackers: --eugene miya NASA Ames Research Center eugene@ames-aurora.ARPA "You trust the `reply' command with all those different mailers out there?" {hplabs,hao,dual,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene draft: The Mythical MIPS (MegaFLOPS) (pardons to Fred Brooks) "Introduction" That's it! I'm tired of hearing about all this parallelism out there. Too many people are talking about parallelism without truly understanding what it is. There appear to be conceptual as well as syntactic and semantic problems. One problem is that the world is not always parallel. "Thinking" is not always parallel: dependency "chains" are created in logic for instance. Another problem is that we think much of the world is parallel, but some "levels" of parallelism are not interchangeable. It appears there are serially connected parallel processes with serial bottlenecks between processes (not necessary Petri nets). Looking at snapshots, I see two communities who are not communicating: physical scientists see "spatial" parallelism: all those difference equations over a given space, they see meshes, but the computer science people (typically the AI and compiler people) see "syntactic" parallelism, they tend to see syntax trees like data flow graphs, for instance. [I do note that rectangular meshes turned on their corners do represent `trees.'] "The Concept" Parallelism is a geometric concept: lines not meeting and equidistant (well..). Parallelism is not a given. `Dependence' prevents `decomposition.' >From Fred Brooks: If it takes a female 9 months to have offspring, then nine females can have one in one month. If a computation takes 9 units of time, then . . . Are the units interchangeable or should we make a distinction in unit type? Are we confusing work and effort? "Terminology" Consider the terminology parallelism, concurrency, multiprocessing, multitasking (this one is really loaded), nonsequential (non-von), etc. There is a lot of different terminology to describe parallelism. I don't think it's necessary to standardize the terminology, but perhaps we should? For instance: Would you place a "tightly-coupled problem" on a "loosely-coupled" multiprocessor? First obvious question is "what's a `tightly coupled problem?'" How do you measure the parallelism? Is it just the count of the number of parallel execution streams? A problem of parallelism is just the degree of decompositibility: even in uniprocessor computer systems, there is such a degree of asynchronous inefficiency, that CPUs wait, that work is really distributed all over the place. Let's change the terminology for a moment to try and better understand the issues. Rather than use parallel and multiprocess (or concurrent) Let's try "cooperative" and "coordinated" like we would take regions around a point, we might be able to study the neighborhood around the word `parallel.' Is there a difference between the two. Diane Smith asserts there is. I think there may be. Cooperative computing implies working together to achieve a single goal. Coordinated computing implies more that processes don't bump heads (separate goals) but work in a common environment (coordinate). There is the obvious third factor of communications. There may also be levels and different types of communications such as control interaction versus bulk transfer. Better adjectives might exist, perhaps changing words do better, but history effects will bias those of us working on this. "Classifications of parallelism" There are an obscene number of classifications: Flynn's system: SISD, SIMD, MIMD... Kuck's modification: execution streams distinct from instruction streams: SIME(MD), MIME(MD), etc. Handler's commentary that there were lots of commentaries and little work Prolog et al AND-parallelism and OR-parallelism Then there is temporal parallelism: pipelining: parallelism, but different Parallelism is all cars starting forward the moment the light turns green (without regard for any cars head). Pipelining is waiting for the car ahead of you to start rolling. I also see three conditions of parallelism: parallelism is not constant. It's like snow and it's many forms: powder, neve, firn, sastrugi, and the Eskimo words. I see Constant parallelism: spatial parallel is a good example, the number of parallel streams does not basically change thru time. Gauss-Seidel and other iterative solutions to systems of equations? AND-parallelism (can be coarse or fine grained (what ever grain means)). Converging parallelism: The number of parallel streams is reducing, perhaps approaching serial: data flow graphs of dot products, of the summation step of a matrix multiply, a Gauss-Jordan (elimination, or direct solution) is another example. Must be fine-grained. Diverging parallelism: (perhaps several types): many forks, OR-parallelism, fractal. Like diverge series, this type of parallelism has problems. (Can be fine or coarsed grained?) The real key is the quantitative characterization (at some level) of parallel-ism. Are we to only count streams? While it is largely a matter of communications/coupling, how do we evaluate the communications needs of an algorithm as opposed to an architecture? What are we going to do with 2-D flow charts where we need to express forking and branching on the same 2-D plane? Oh well! Still searching for an honest definition. "Socio/politico/economic commentary" Recent economically based events in parallel processing are amazing. The number of companies actively marketing hypercube arcitectures and Crayettes is stagering. Machine with Cray class power are not surprising, this is inevitable. Cray instruction set compatable machine offerings is what is surpising about this. There are so few Crays (100) out there, that the half dozen or more companies who say they are offering such guarantee failure. More surprising are the number of hypercube architectures. Admittedly, hypercubes offer very nice connectivity features, but only one person has a good perspective: Justin Rattner, Intel, who offered the machine as an experimental testbed not a Cray alternative. What with all this talk about parallelism, it is surprising there are not more companies marketing, designing, etc., mesh-type architectures ala ILLIAC IV style architectures. That spatial model of parallelism (SIMD) is probably the easier to build if not program. This latter point is worth some debate, but as noted many models of parallelism are spatially based. Only the MPP, the DAP, and it seems the Connection Machine to a somewhat lesser extent are based this way (albeit more connections). It would be argued by some that this is for more limited applications but again those are spatially based problems tned to dominate. Why no 68Ks or 32Ks in a mesh? Is it all marketing hype? How could the money be better directed (for research purposes since obviously some of this money is bound to go into failed experiments [necessitated by empirical work]), can we spread out the "cost" to develop new architectures. Ah yes, reinventing the ILLIAC again. "A few asides:" [From S. Diane Smith] When asked about the interconnection network in MPP compared to that of the STARAN, Ken Batcher replied, "We learned that you didn't need all that (the multistage cube/omega) for image processing, that a mesh was good enough." You could look at MPP as a second generation parallel processor, even if the processors are only 1 bit wide. They got rid of a number of "mistakes" that they learned about through STARAN. The "tightly coupled" .vs. "loosely coupled" debate went on 7-8 years ago before everyone got tired of it. It was sort of the analog of the RISC vs. CISC debates of today. The net result was sort of an agreement that there was a spectrum, not a dicotomy. There have been one or two papers on classification, none very satisfying. I'll see if I can't find them. The latest thing you see in parallel processing is the "real" numerical analysts who are actually putting the problems on machines. Until very recently, with a few exceptions from the ILLIAC days, most parallel numerical analysis has been theoretical. Diane. . . ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Fri Jun 27 18:47:42 1986 Date: Fri, 27 Jun 86 18:47:38 edt From: vtcs1::in%<> (LAWS@SRI-AI.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #158 Status: R AIList Digest Thursday, 26 Jun 1986 Volume 4 : Issue 158 Today's Topics: Literature - AIList in Technology Review & AI Expert, AI Tools - Turbo Prolog & Language Paradigms, Psychology - Memory in Bees & Creativity & Forward Following, Policy - Covert Ads ---------------------------------------------------------------------- Date: Wed 25 Jun 86 16:43:41-PDT From: Ken Laws Subject: Technology Review AIList is the subject of the First Line column (by John Mattill) in the May/June 1986 issue of MIT's Technology Review, p. 2. John is commenting on our discussion of the Dreyfus' article in their January issue, and finds our "electronic gossip" an intriguing publication channel. He quotes Peter Ladkin and me, and also Brad Miller's "In 3,000 years philosophy has still not lived up to its promises, and there is no reason to think it ever will." (He unfortunately lists it as anonymous.) The editorial is followed by a letters column, from which I particularly liked A. DeLuca's comment: "Granted, the mind is not like a computer. But an airplane is not like a bird, either." -- Ken Laws ------------------------------ Date: Mon, 23 Jun 86 14:10:48 CDT From: Glenn Veach Subject: Summarizing "AI Expert" The following is a summary/personal comment, of the "Premier Issue" of "AI Expert" presented as "The Magazine for the Artificial Intelligence Community." As the editor, Craig LaGrow, notes it is "rare to find such a strong response from advertisers" and "quality submissions" of articles in the first run of a new magazine (particularly in the computer field with our overwhelming number of upstart publications). The advisory board of the magazine is quite impressive with the likes of John Seely Brown of Xerox PARC, Carl Hewitt of MIT, Earl Sacerdoti of Teknowledge, Donald Waterman of Rand, and Terry Winograd of Stanford, to name a few. With the commitment of such names one should expect to to see a quality publication. The feature articles as well as the "regular columns" are well written and contributed by knowledgeable authors. A feature for which the publisher should be commended, is the inclusion in many of the articles of actual code which demonstrates the technique or program which the author is presenting. By the way, the code is reportedly available for downloading from four different sources, for those who wish to try it out. Following is an annotated list of articles and columns: "Brain Waves" a column by Larry Geisel/CEO Carnegie Group Inc. in this article he writes on "The AI Explosion: A Response to National Priorities" "AI Insider" a column capsulizing industry and academic developments by Susan J. Shepherd a consultant with Academy for Educational Development "Expert's Toolbox" a column written by Jonathan Amsterdam a grad student at MIT writes an article on "Augmented Transition Networks for Natural Language Parsing" which includes code for an ATN compiler and a sample ATN grammar. "AI Apprentice" a column by Bill and Bev Thompson free-lance writers and consultants write on "PROLOG From the Bottom Up" which introduces PROLOG and the basic logical concepts, includes some basic coded procedures. "Control Over Inexact Reasoning" a feature article by Koenraad Lecot a grad student at UCLA and D. Stott Parker a prof. at UCLA. "Concurrency in Intelligent Systems" a feature by Carl Hewitt of MIT. "Rule-Based Programming in OPS83" a feature by Dan Neiman with ITT Advanced Technology Center and John Martin of Philips Laboratories. Includes code for a short program. "Multitasking for Common LISP" by Andrew Bernat of the University of Texas at El Paso. Includes code for the concurrent processing modules. "In Practice" a column by Henry Eric Firdman a consultant uses this column to look at the use of AI in real-world business applications. This issue's article -- "Components of AI Systems". "Software Review" a column by Darryl Rubin of Microsoft. Here we get a look at "Turbo PROLOG: A PROLOG Compiler for the PC Programmer." "Book Store" a column by Lance B. Eliot, director of UCLA's Expert Systems Laboratory gives short blips on four "classics". "AI Expert" will be published monthly beginning in October. The above is a sample of what they have to offer at this time. If they continue to produce similar articles it should be of interest to most in the AI community and especially those in industry seeking to apply AI to their needs, as well as to those just starting to "get into" the field. Subscription info: AI Expert PO Box 10952 Palo Alto CA 94303-0968 charter first year at $27.00 for the 12 issues. ------------------------------ Date: Sun, 22 Jun 86 12:54:16 mdt From: ted%nmsu.csnet@CSNET-RELAY.ARPA Subject: turbo prolog Recent reviews have correctly pointed out that turbo prolog's attempt to enforce type checking has both good and bad points and that the speed is not very impressive, since much of the unification can be done at compile time if data types are known. The major difficulty with Borland's approach to adding strong typing to prolog is the loss of higher-order predicates. Since a domain can be at most the disjunction of a small number of _predeclared_ terms, it is impossible to write a general higher- order procedure. This means that you can't write findall, as described in Clocksin and Mellish (Borland has of course, in their wisdom, provided such a function). The function doall also cannot be written. It is handy as a substitute for findall when the predicate Q is executed for effect only. doall(Q) :- Q,fail. doall(_). First class procedural objects are, in many senses, a much more fundamental distinction between symbolic and conventional languages than are heap allocated data structures. Their loss makes many advanced applications nearly impossible. ------------------------------ Date: 24 Jun 86 11:51:26 GMT From: decvax!mcnc!duke!jds@ucbvax.berkeley.edu (Joseph D. Sloan) Subject: Language paradigms > Can anyone supply me with pointers to readable introductions > to access-oriented programming? How about articles or > books on programming paradigms in general? Reply by mail > and I will summarize results if there is enough interest. > Joe Sloan, > Box 3090 > Duke University Medical Center > Durham, NC 27710 > (919) 684-3754 > duke!jds, As promised, a highly edited summary follows. Many thanks to all who replied. _______________________________________________________________________________ You probably want to find out about a programming system called LOOPS which was made at PARC in 1981. It combines Procedure-Oriented (like Lisp) with Object Oriented (like Smalltalk) with Access Oriented (a program monitors another and gets triggered when a value changes (good debuggers have watchpoints)), and Rule-oriented (like production/expert systems). Bobrow, et al., The LOOPS manual. Tech Rep. KB-VLSI-81-13, Knowledge Systems Area, Xerox Palo Alto Research Center. _______________________________________________________________________________ There is a special issue of IEEE SOFTWARE (Jan '86) on "multiparadigm languages and environments" which may be of some help to you. _______________________________________________________________________________ AA programming's also mentioned briefly in "Knowledge Programming in LOOPS: Report on an Experimental Course", by Stefik, Bobrow, Mittal, and Conway, in AI Magazine, Fall 1983. _______________________________________________________________________________ Bobrow, D. G. and Stefik, M. "Perspectives on AI Programming", Science Feb. 28, 1986 Stefik, M. Bobrow, D. and Kahn, K., "Integration of Access Oriented Programming in a Multiparadigm Environment", IEEE Software, January 1986 Stefik, M. and Bobrow, D. G. "Object Oriented Programming, Themes and Variatations" AAAI Magazine, Winter 1986 _______________________________________________________________________________ You might like to chase up the work of Kristen Nygaard if you are not already familar with it. As one of the designers of Simula, he can reasonably be said to have invented the whole idea of Object Oriented Programming - about 30 years ago! I suggest you follow up references in 10th ACM POPL and 11th Simula-67 Users' conference. Also Sigplan 20.6. There's also a paper in "Integrated Interactive Computing Systems" Delgano & Sandewall (Eds), North Holland 1983. _______________________________________________________________________________ Very worthwhile reading and examples can be found in: The Structure and Interpretation of Computer Programs Abelson & Sussman MIT Press, 1985 A couple of watershed papers are: Control Structures as Patterns of Passing Messages Carl Hewitt Journal of AI, V8 #3, (also, I believe, in: AI, a MIT Perspective) Definitional Interpreters for Higher Order Programming Languages John Renolds Proc. ACM Annual Conf. Aug '72 Reflection and Semantics in Lisp Brian Smith ACM POPL 11, 1984 _______________________________________________________________________________ An excellent book on the structure and superstructure of programming is ``A practical handbook for software development'' by N.D.Birrell and M.A.Ould, Cambridge University Press, 1985. The book is based around the dataprocessing environment, but can, and should be, applied outside that area. ------------------------------ Date: Wed, 25 Jun 86 09:26 EDT From: Seth Steinberg Subject: Re: Doing AI Backwards Yes, memory seems to be a scarce resource. There was an article in Science on learning in bees, which explains that bees tend to collect pollen from one type of flower during a period of time because there is a cost to learning about a new one. In addition, learning a new flower squeezes out knowledge about other previously learned flowers. In other words, a bee can be an expert on one kind of flower at a time because of memory limitations. There have been a number of interesting bee articles lately. Writing a computer system to emulate a bee's behavior might be an interesting approach. Apparently they can recognize landmarks, learn approaches to flowers, learn which flowers are obnoxious, communicate locations of pollen, reason about locations and a host of other things, all in a brain comparable in size to a large IC. Seth P.S. Oh yeah, read the next message. That's right .... ------------------------------ Date: 25 Jun 86 08:04 PDT From: Newman.pasa@Xerox.COM Subject: Re: Creativity & Analogy Take a look at the chapters on this topic in Douglas Hofstadters book "Metamagical Themas" for an interesting discussion. >>Dave ------------------------------ Date: Wed 25 Jun 86 13:02:17-PDT From: Pat Hayes Subject: Re: AIList Digest V4 #157 Brian Gaines and I were once both faculty in the same University, and he explained an interesting and effective technique of leadership called following from the front. It works like this: suppose one is with a group of people in a strange place, but someone in the group knows the area: and its time to go somewhere ( say, to lunch ). Then set off confidently in some direction or other as though leading the group to the right place. They will follow you. If its the right way, no problem. If its the wrong way, the person who knows the right way will say something about how he thinks the right way is over there..at which point you say something like " h yes, of course!" and go in the right direction. With a little intelligence applied to the initial guess, and some practice at conversational bluffing, this can be quite effective. The end result is that you learn the layout of the strange area and everyone else in the group thinks of you as someone worth following. I've seen Brian do this, and it works. Of course, it works best in areas which have little internal structure and where anyone with a bit of common sense and a gift with words can come up with something which sounds like a good direction to move in, and where nobody knows the right way anyway. Pat Hayes [There is a related "psychic" technique called muscle reading. The psychic leaves the room and some object is selected. The psychic returns, grabs someone's arm, and begins leading him rapidly around the room. Soon they arrive at the selected object and the psychic identifies it. The trick, which is reportedly easy to learn, is that the subject being led provides inertial clues due to his anticipation of search path. Belief in the psychic's ability may help, but rapid motion is sufficient to produce reflexive muscle responses. -- KIL] ------------------------------ Date: Wed 25 Jun 86 11:40:31-PDT From: Pat Hayes Subject: Policy - Covert Ads I know I've flamed about this before and been answered at length, but Matt Hefrons "query" irritated me. I haven't seen such a good advertisement masquerading as something innocent since watching Masterpiece Theatre. Matt wants to survey marketed expert systems: fine. Is it really necessary to tell us that SxxxPxxx is such a one ( NOT, he is careful to point out to us, a mere shell ), marketed by some company ( whose name he is careful to spell out for us ), and which ( just in passing we can infer ) runs on - gosh - a PC. The query could have been stated quite clearly without all this commercial hype spraypainted over it. Pat Hayes ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Wed Jul 2 00:45:28 1986 Date: Wed, 2 Jul 86 00:45:25 edt From: vtcs1::in%<> (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #159 Status: R AIList Digest Tuesday, 1 Jul 1986 Volume 4 : Issue 159 Today's Topics: Seminars - Chunking and XAPS3 (Rutgers) & Advanced Planning Systems (Rutgers) & Real-Time Inferencing with Adaptive Logic Networks (NASA) & Overview of the MENTOR System (CMU), Conference - ACM Conference on Office Information Systems ---------------------------------------------------------------------- Date: 23 Jun 86 10:51:24 EDT From: Tom Fawcett Subject: Seminar - Chunking and XAPS3 (Rutgers) The summer machine learning discussion group meets Tuesdays at 11 in room 423. This week John Bresina will give a talk on "Chunking and XAPS3". The abstract follows. [...] In this talk I discuss the chunking theory of learning, and in particular how this theory is realized in the XAPS3 production system architecture. The talk is based on Paul S. Rosenbloom's Ph.D. thesis, "The Chunking of Goal Hierarchies: A Model of Practice and Stimulus-Response Compatibility" [Carnegie-Mellon, 1983], for which Allen Newell was the advisor. First the chunking theory of learning is described and the desired behavioral aspects of a chunking mechanism are summarized. I then present the architectural constraints that an implementation must satisfy in order to exhibit this desired behavior. Next the XAPS3 production system architecture is described, followed by a detailed look at the implementation of the chunking theory within XAPS3. In conclusion I present a brief critique of this implementation as well as some suggestions for extending and improving it. ------------------------------ Date: 23 Jun 86 14:43:33 EDT From: Smadar Subject: Seminar - Advanced Planning Systems (Rutgers) III SEMINAR Title: Advanced Planning Systems Speaker: Chitoor V. Srinivasan Date: Friday, June 27, 2:50 PM Place: Hill Center, Room 705 Dr. Srinivasan, a professor in our department, will present his current research in an informal talk. Here is his abstract: A new planning technique for planning in "dynamic worlds" is introduced in this talk. It develops plans using a method of approximate reasoning and plan refinements over abstraction spaces, and is based on a formalization of the problem solving approach which Navy planners use to design Naval Operational Plans. A dynamic world is one in which changes occur not only in the properties associated with the objects that exist in the world, but the set of objects existing in the world itself may change. As the world changes some objects may get destroyed and others may get newly created. It is a world in which reasoning about multiple actions occuring simultaneously over intervals of time is necessary to do planning. Also, knowledge needed to do planning in such worlds may be only incompletely known. Existing planning systems do not consider worlds of this kind. In the new planning technique plans are viewed as hierarchies of "behaviors" to be realized by actions that occur in a world. Behaviors are properties (usually dynamic ones), which (a). remain invariant while worlds themselves change as a result of actions occurring in them, and (b). are needed for the success of one or more of those actions, or are intrinsic properties of the worlds themselves. Of course, a given behavior may be the result of several actions occurring simultaneously. Thus for example, "an object will continue to move in a straight line, unless disturbed by force" is a general behavior of movements which is an intrinsic property of the world we live in. "Goods transported will eventually appear in neighborhoods progressively closer to destination" is a general behavior of transportation actions. This concept of behavior is formally defined here and a formal action language is introduced to describe actions in terms of "[preconditions, behaviors, functions]." It gives rise to a new "modal action calculus" which is quite different from both "situation calculus" and calculus of "dynamic logic." It is shown how this concept of \fIbehavior\fR makes it possible to develop plans in dynamic worlds through a process of successive plan refinements. ------------------------------ Date: Mon, 30 Jun 86 12:49:03 pdt From: eugene@AMES-NAS.ARPA (Eugene Miya) Subject: Seminar - Real-Time Inferencing with Adaptive Logic Networks (NASA) National Aeronautics and Space Administration Ames Research Center AMES AI FORUM SEMINAR ANNOUNCEMENT SPEAKER: Jacques J. Vidal University of California, Los Angeles TOPIC: REAL-TIME MULTISENSOR INFERENCING WITH ADAPTIVE LOGIC NETWORKS The talk will present a general architecture model for special-purpose parallel processing networks that perform logical inferences in real-time. Operation is divided beween two complementary modes: Adaptation (programming) and Processing. The data processing mode is a hierarchical, asynchronous and completely parallel dataflow. Typically, logic operations stored in a dynamically reconfigfurable combinatorial network, are performed on sensor data. In the adaptation mode the network incrementally receives goal information (either from a human user or directly from environment sensors), and the node functions and/or connections self-adapt in order for the output(s) to continually satisfy the externally defined goal. Adaptive control is sequential, but performed in a distributed and largely concurrent manner by the network nodes. The target applications are event-detection, malfunction management and similar robot functions, including vision. DATE: Thursday, TIME: 1:00 - 2:00 pm BLDG. 239 Room B39 July 10, 1986 -------------- (Basement Conf. Room) POINT(S) OF CONTACT: Lee Duke PHONE NUMBER: (805) 258-3802 NET ADDRESS: duke%ofe@ames-io.arpa or Alison Andrews (415) 694-6741 andrews%ear@ames-io.arpa (PLEASE NOTE ALISON'S EMAIL ADDRESS CHANGE! ^ ) VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor Reception Building (N-253) or the Security Station near Gate 18. Do not use the Navy Main Gate. Non-citizens (except Permanent Residents) must have prior approval [...] ------------------------------ Date: 26 Jun 86 17:07:07 EDT From: Marcella.Zaragoza@isl1.ri.cmu.edu Subject: Seminar - Overview of the MENTOR System (CMU) SPECIAL SEMINAR Topic: OVERVIEW OF THE MENTOR SYSTEM Speaker: Bernard Lang, INRIA Place: WeH 8220 Date: Monday, June 30 Time: 11:00am - 12:00noon Mentor is a structured document manipulation system based on a representation of documents as abstract syntax trees. After an overview of the first implementation of Mentor and of the experience acquired with its use for the development and maintenance of programs and languages, we shall present some of the new developments underway. A new version of the system is now being developed in a Lisp dialect (Le_Lisp) in an object oriented style, with a strong emphasis on the realisation of a complete kernel for abstract syntax tree manipulation (user interfaces being developed independantly). The language Typol for semantics specification, and the language PPML for pretty-printers specification shall be briefly introduced. ------------------------------ Date: Mon, 23 Jun 86 12:12:07 edt From: rba@petrus.bellcore.com (Robert B. Allen) Subject: Conference - ACM Conference on Office Information Systems ACM CONFERENCE ON OFFICE INFORMATION SYSTEMS October 6-8, 1968, Providence, R.I. Conference Chair: Carl Hewitt, MIT Program Chair: Stan Zdonik, Brown University Keynote Speaker: J.C.R. Licklider, MIT Distinguished Lecturer: A. van Dam, Brown University Panels and Sessions Advanced Computational Models AI in the Office Impacts of Computer Technology on Employment Organizational Analysis: Due Process Future Directions in Office Technology Comparison of Social Research Methods Organizational Analysis: Organizational Ecology Models of the Distributed Office Interfaces For more information, call the Conference Registrar at Brown U. (401-813-1839), or send electronic mail to mhf@brown.CSNET. ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Wed Jul 2 06:43:30 1986 Date: Wed, 2 Jul 86 06:43:26 edt From: vtcs1::in%<> (LAWS%SRI-AI.ARPA@SRI-STRIPE.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #160 Status: R AIList Digest Tuesday, 1 Jul 1986 Volume 4 : Issue 160 Today's Topics: Queries - Expert Systems for Classification & Intelligent Databases & Constraint-Propagation Inference Engines, Education - Special J. Instructional Science Issue, Review - The Evidence of the Senses, Philosophy - Creativity and Analogy ---------------------------------------------------------------------- Date: 27 Jun 1986 10:55-PDT From: balaji@usc-cse.usc.edu Subject: Expert systems for evolutionary classification of fish I am sending this message for a friend. I will forward replies to her. Thanks. Balaji I am writing a LISP program to classify fish and determine their evolutionary history. This involves nesting species of fish into a hierarchical taxonomic arrangement, on the basis of characteristics shared among the species. My program will need to determine whether characteristics are primitive or advanced, in order to determine how they fit into the taxonomic hierarchy. This requires some degree of heuristic reasoning and this part of the program will probably be constructed as a mini expert system. The nesting process (i.e. arranging the species in a taxonomic hierarchy) is a more or less standard procedure, but requires flexibility to utilize heuristics in some cases. To get a better idea of how to go about writing my program, I would like to find out about existing programs that deal with issues similar to mine. If anyone has any suggestions about where I might find AI systems that might help me, or papers on such systems, I would be most appreciative if they send me a message. Thank you. Noelle Sedor ------------------------------ Date: Sun, 29 Jun 86 23:27:21 CDT From: wucs!wucec2!grs0473@seismo.CSS.GOV (Guillermo Ricardo Simari) Subject: Intelligent Databases If you could add only one feature to a commercial relational DBMS in order to make it more "intelligent", what would be your choice? If I got enough answers I'll post a summary. +------------------------------------------------+ | ihnp4!cuae2!ltuxa!we53!wucs!wucec2!grs0473 | | | | Guillermo R. Simari | | P.O.Box 3257 | | Saint Louis, MO 63130-0657 | +------------------------------------------------+ ------------------------------ Date: 30 Jun 86 09:27 EDT From: Siems @ DCA-EMS Subject: constraint propagation inference engines jerry feinstein and david bailey of booz, allen, and hamilton are interested in any work being done in the area of constraint propagation that might be applied to inference engines. the specific interest is in the use of tight constraints and a non-optimizing, simplex-like algorithm to find a quick, "satisficing" solution in an ordered, though not necessarily numeric, problem space. this is a follow-up on the constraint propagation workshop held at the expert systems conference in avignon in april of this year. any information on current work in this area or on the use of constraint propagation in inference engines would be greatly appreciated. thank you. david bailey booz, allen, and hamilton 4330 east west highway bethesda, md 20014 (301)951-2155 ------------------------------ Date: Wed, 25 Jun 86 09:50:07 edt From: Bob Lawler Subject: Notice of journal issue [Forwarded from the AI-Ed Digest by Laws@SRI-AI.] Dear Colleagues, Today I received from Elsevier a special issue of the Journal of Instructional Science on the theme of "AI and Education". This double- number volume (several hundred pages in length) was prepared by Masoud Yazdani (University of Exeter) and myself (Bob Lawler) as a preliminary collection of articles prepared for the Second International Conference on AI and Education held at Exeter University in September 1985. The issue is Volume 14, Nos. 3 and 4, dated May, 1986. A more comprehensive book on the theme will be forthcoming at the end of 1986. The contents of the special issue are as follows: M. Yazdani and R. Lawler AI and Education: an overview A. DiSessa Artifical Worlds and Real Experience W. Feurzeig Algebra Slaves and Agents in a Logo-based Mathematics Curriculum R. Lawler and G. Lawler Computer Microworlds and Reading H. Lieberman An Example Based Environment for Beginning Programmers S. Ohlsson Some Principles of Intelligent Tutoring J. Self The Application of Machine Learning to Student Modelling A. Priest Solving Problems in Newtonian Mechanics G. Drescher Genetic AI: translating Piaget to Lisp K. Carley Knowledge Acquisition as a Social Phenomenon If you are interested in having a copy of this journal, write to: Elsevier Science Publishers Science and Technology Division P.O. Box 330 1000 AH Amsterdam The Netherlands The price for this double-issue of the journal is $57.25, which includes air transport to the US and surface mail on the continent. Bob Lawler (LAWLER at GTE-LABS on CSNET) (LAWLER at MIT-OZ through MIT-MC on ARPANET) ------------------------------ Date: Sat, 28 Jun 86 20:41:12 -0200 From: Eyal mozes Subject: Book review: "The Evidence of the Senses" "The Evidence of the Senses" by David Kelley Louisiana State University Press, 1986, 262 pp., $27.50 "The Evidence of the Senses: a Realist Theory of Perception" is a comprehensive philosophical treatment of perception, integrating classical and recent work in philosophy and psychology. To those who agree with its conclusions, it offers a sound, detailed framework for psychological, biological and AI work in perception; to those who don't, it offers an illuminating, profound and thought-provoking alternative theory. Dr. Kelley is formerly an assistant professor of philosophy and member of the Cognitive Science program at Vassar College, and currently a senior research fellow of the Ayn Rand Institute. His work is based on the philosophy of Objectivism. Almost all contemporary work in the theory of perception, including the writings of philosophers, is devoted to detailed consideration of specific issues, while taking for granted a wider context of basic philosophical assumptions. In sharp contrast to this procedure, Dr. Kelley makes his own basic assumptions fully explicit, defends them on general philosophical grounds, and only then applies them to specific issues. This makes it possible for him, when arguing against opposing views, to argue in terms of essentials by recognizing the basic - often hidden - assumptions on which these views and the arguments for them rely. A central theme of the book is the rejection of the "diaphanous model of awareness" - the view that awareness of objects can't be mediated by any process whose nature affects the way the objects appear; Dr. Kelley demonstrates that this model has been accepted, explicitly or implicitly, by almost all philosophers of perception since Kant, and it is the root of all three common views of perception: naive realism, which claims that our sensory apparatus is indeed diaphanous, and has no effect on the appearance of external objects; representationalism, which claims that we don't perceive external objects, but internal representations which give information about these objects; and idealism, which denies the existence of external objects. Chapter 1 sets up the general epistemological framework for the book; Dr. Kelley contrasts the diaphanous model with his own basic assumption, "the primacy of existence" - the principle that consciousness is the faculty of perceiving existence - which dispenses with the need for making any prior assumptions about how consciousness "should" work. Chapters 2 through 5 apply this principle to perception. Chapter 2 deals with the relation between perception and sensation; Dr. Kelley challenges the "sensationalist" approach - including its modern "computational" version - which claims that perception is a process of inference on sensations; he provides philosophical support for James Gibson's theory of "direct perception" - which holds that external objects are perceived directly, and that perception is a distinct form of awareness, not composed out of sensation - and answers the major criticisms against Gibson. Chapter 3 treats the relation of an object to its sensory qualities. The treatment is based on Ayn Rand's concept of "form of awareness", which designates all perceived qualities which are relative to the perceiver, distinguishing them from the perceived object and its intrinsic properties; Dr. Kelley uses this concept to demonstrate the consistency of perceptual relativity with direct realism, and illustrates the principle in a discussion of visual illusions and in a detailed treatment of colors; he then treats in this framework the traditional distinction of primary vs secondary qualities. Chapter 4 uses the principles established in previous chapters to answer the major arguments for representationalism; this includes a discussion of hallucinations and their relation to perception. Chapter 5 concludes the discussion of perception by giving a full definition - "perception is direct awareness of discriminated entities by means of patterns of energy absorption by sense receptors" - and discussing in detail each element in the definition and its implications for each of the five senses. Chapters 6 and 7 deal with perceptual knowledge, and the role of perception as the base of conceptual knowledge. Chapter 6 discusses the two common theories about the nature of justification: the "foundational" theory, which holds that propositions about experiential states are self-justifying and provide the foundation on which all other knowledge is built as a hierarchy; and the "coherence" theory, which holds that no single proposition can be justified outside the context of the rest of a man's knowledge, and that the only way to justify knowledge is by its self-consistency. Dr. Kelley identifies and challenges the common premise implicit in both these positions - "the propositional theory of justification", which holds that the only way to justify a proposition is by inference from other propositions. Chapter 7 deals with "perceptual judgments" - conceptual identifications of perceived entities and their attributes. Dr. Kelley's treatment of this subject is not complete, and he does not offer a full theory; but he does indicate the direction such a theory should take, and its implications for concept-formation. He discusses the relation between the perceptual discrimination of an entity and the reference to it in a perceptual judgment; the difference between "construction" and "discovery" models of concept-formation, and their relation to the possibility of justifying a perceptual judgment without need for an inference from other propositions; the implications of perceptual relativity for forming concepts of sensory qualities; and the autonomy of perception, answering the various philosophical and scientific arguments for the claim that perception and perceptual judgments are affected by previous knowledge or desires. The book is thoroughly organized, with careful attention to integration of the various issues and to illustration of the abstract points; the result is that, despite its highly technical content, it is very readable. All technical terms are carefully explained, and therefore, while reading the book will be easier for those with a previous background in the theory of perception, such a background is not necessary. The book contains extensive surveys of previous work and of different views and arguments, with heavy use of references, and this makes it an ideal starting-point for a study of the subject. In conclusion, I strongly recommend this book to anyone seriously interested in the theory of perception, and I think it is a must read for any psychologist, biologist or AI researcher whose work involves this subject. Eyal Mozes BITNET: eyal@wisdom CSNET and ARPA: eyal%wisdom.bitnet@wiscvm.ARPA UUCP: ..!ucbvax!eyal%wisdom.bitnet ------------------------------ Date: Fri, 27 Jun 86 11:23:52 edt From: Jay Weber Reply-to: jay@rochester.UUCP (Jay Weber) Subject: Re: Creativity and Analogy > Yes, I do want to understand "creativity" in terms of less slippery >concepts, such as "analogy". We are forced to start with informal >approaches but hope to find more formal definitions. I do not >understand why a formal approach would satisfy very few people or >why an informal approach would serve no useful purpose. Consider the following view of analogy, consistent with its formal treatment in many sources. A particular analogy, e.g. that which exists between a battery and a reservoir, is a function that maps from one category (set of instances) to another. Equivalently we can view this function as a relation R between categories, in this case we have a particular kind of "storage capability". This relation is certainly 1) reflexive. "A battery is like a battery" (under any relation) 2) symmetric. "A battery is like a reservoir" implies "A reservoir is like a battery" under the same relation R 3) transitive. "A battery is like a reservoir" and "A reservoir is like a ketchup bottle" imply "A battery is like a ketchup bottle" WHEN THE SAME ANALOGY HOLDS BETWEEN THEM (same R). Then any analogy R is an equivalence relation, partitioning the space of categories. Each analogy corresponds to a node in an abstraction hierarchy which relates all of the sub-categories, SO THE SPACE OF ANALOGIES MAPS ONTO THE SPACE OF ABSTRACTIONS, and so under these definitions analogy and abstraction are equivalent. Now to the point: I recently presented this sketched proof to my peers and they fought me whenever I tried to say "this is what analogy is" rather than "this is what I define analogy to be" (with the latter claim I probably should use a different term like R-analogy or XYZZY). I fact, no one could agree to a particular formal definition of the term "analogy", since we all have individual formal definitions by virtue of the fact that we will answer yes or no when given a potential analogy instance, so we are formal language acceptors with our senses as input. This is what I mean by a "slippery" term, i.e. one that has drastically different meanings depending on its user. This is why I say a formal definition of analogy would satisfy very few people. Informal definitions are useless because by defintion there is no notion of a valid inference from the theory, we cannot make predictions with them and therefore cannot do science with them (most "loose" defintions of things put forward do have some formal properties, but one must be careful). >I am sure that you do not imply that an analysis (formal or informal) >of >anything< is futile. What is it about "creativity" that makes its >analysis a no-win proposition? "Creativity" is VERY slippery, perhaps only slightly less slippery than "intelligence". Profit by Turing's example and keep your personal definition of the slippery term in mind but define a new one, e.g. Turing-test-intelligence instead of asking for a definition of the word in usage. Jay Weber Department of Computer Science University of Rochester Rochester, N.Y. 14627 jay@rochester.arpa ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jul 8 00:55:41 1986 Date: Tue, 8 Jul 86 00:55:36 edt From: vtcs1::in%<> (LAWS%SRI-AI.ARPA@SRI-STRIPE.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #161 Status: R AIList Digest Monday, 7 Jul 1986 Volume 4 : Issue 161 Today's Topics: Conferences - Test and Evaluation Assoc. AI/Expert System Workshop & Theoretical Issues in Natural Language Processing & Database Theory 1986 - Program ---------------------------------------------------------------------- Date: Wed, 2 Jul 86 21:07 EDT From: HCGRS%clemson.csnet@CSNET-RELAY.ARPA Subject: Conference - Intl. Test & Evaluation Assoc. AI/Expert System Workshop INTERNATIONAL TEST AND EVALUATION ASSOCIATION Artificial Intelligence/Expert System WORKSHOP AI/ES WORKSHOP PROGRAM July 8-10, 1986 George Washington University PHONE REGISTRATION (703) 893-0228 Tuesday, 8 July Morning Session 0830-0840 - Welcome John Bolino, President ITEA 0840-0850 - Welcome President, GWU 0850-0900 - Admin (if any) Henry Alberts, ITEA Staff 0900-0940 - KEYNOTE Barry Silverman, GWU 0940-0950 - Coffee Break 0950-1030 - TIMS Dr. Peter McWhite, GRC 1030-1110 - TACTICAL AI Dr. Stuart Brodsky, Sperry 1110-1145 - APPLICATION OF Dan McDonough, USAF-AFOTEC AI TO OT&E Luncheon at the University Club, Marvin Center Afternoon Session 1330-1630 - 30-40 person groups "Hands-On" sessions with morning speakers and their systems. Wednesday, 9 July Morning Session 0830-0840 - Announcements Henry Alberts, ITEA Staff 0840-0920 - AUTO SWITCHING Ms. Marquerite Denocourt, BELLCOM 0920-1000 - TESTPRO Dr. Anthony Mucciardi, Infomatics 1000-1020 - Coffee Break 1020-1100 - NATC TECHMAN Mr. George Hurlburt,USN/NATC PAX Dr. Joel Simkol, GWU Luncheon at the University Club, Marvin Center Afternoon Session 1330-1630 - 30-40 person groups "Hands-On" sessions with morning speakers and their systems. Thursday, 10 July Morning Session 0830-0840 - Announcements Henry Alberts, ITEA Staff 0840-1145 - Panel Discussion Panelists: Charles K. Watt Georgia Tech Richard A. Demilo Georgia Tech Barry Silverman GWU H. Steve Kimmel ODUSDRE(T&E) 0840-0940 - Panel Opening Statements 0940-1010 - Coffee Break 1010-1145 - Open Discussion between Panel and Audience 1140-1200 - Closing Remarks John Bolino, President ITEA Luncheon at the University Club, Marvin Center Afternoon Session 1330-1445 - 30-40 person groups "Hands-On" sessions with speakers and their systems. Evening Session 1500-1700 - Movie & Tour - Air & Space Museum, Museum Staff 1730-1930 - General Discussion - U.S. Senate Caucus Room Hon. John Warner, Senate Armed Services Committee -- Sponsor -- Dr. Harold C. Grossman Dept. of Computer Science Clemson University Clemson, SC hcgrs@clemson.csnet ------------------------------ Date: Thu, 3 Jul 86 15:21:59 mdt From: yorick%nmsu.csnet@CSNET-RELAY.ARPA Subject: Conference - Theoretical Issues in Natural Language Processing CC C R R R L C O M P U T I N G CC R R L R E S E A R C H C R R L L A B O R A T O R Y CC R R L CC R R L Box 3 CRL CC C R R LLLLLLLL NMSU, Las Cruces 88003 Tinlap3 January 7,8,9, 1987 Tinlap3 will be the third in the series of interdisciplinary workshops Theoretical Issues in Natural Language Processing. The format will be as in MIT(1985) & Illinois (1978): invited panels of distinguished figures in the field will discuss pre-circulated statements of position. Lively audience participation is anticipated. The panels are intended to cover the major contentious issues of the moment. Tinlap3 is being supported by the Association of Computational Linguistics and funds are also being sought from NSF, AAAI, and ACM. Tinlap Grand Committee: Nick Cercone (Simon Fraser University), Richard Rosenberg (Dalhousie University), Roger Schank (Yale University), David Waltz (Brandeis University), Bonnie Webber (University of Pennsylvania). Tinlap3 General Chair: Andrew Ortony (University of Illinois) Tinlap3 Program Chair: Yorick Wilks (New Mexico State University) Panels and their Chairs will be: * Connectionist and other parallel approaches to natural language processing (Dave Waltz, Thinking Machines & Brandeis) * Unification and the new grammatism (Fernando Pereira, SRI) * World and world representations (Don Walker, Bellcore) * Formal versus commonsense semantics (Yorick Wilks, NMSU) * Why has theoretical NLP made so little progress? (to be confirmed) * Discourse theory and speech acts. (Barbara Grosz, SRI) * Reference: the interaction of language and the world (Doug Appelt, SRI) * Metaphor (Derdre Gentner, U.Illinois) * Natural language generation (Aravind Joshi, U. Pennsylvania) Registration: Registration covers pre-circulated preprints, mid-session refreshments etc., some local transportation, and adminstration. Registration fees: Non-student: $50 ($40 if registered before Aug. 20, 1986) Full-time students: $30 ($25 if registered before Aug. 20, 1986) Registration Form: [Deleted -- contact author for copy. -- KIL] Registrants should fill out and print out form, sign and send hardcopy with check made payable to NMSU Foundation to Tinlap3, Box3CRL, NMSU, Las Cruces, NM 88003. Sending a copy of your registration by return netmail will also assure its quick entry to mailouts of further materials. Where: at New Mexico State University main campus (Las Cruces), Rio Grande Corridor for Technical Excellence, Computing Research Lab. (505-646-5466) for further details. Forming the western corner of a triangle with White Sands and El Paso, Las Cruces is a city of about 50,000 people in southern NM. Las Cruces is situated between the spectacular Organ Mountains fifteen miles to the east, and the historic Rio Grande River to the west. Two miles west of Las Cruces, near the Rio Grande, is La Mesilla, the old Mexican village where the Gadsden Purchase was signed. The town square is bordered by restaurants and shops, with Indian arts -- pottery, paintings, jewelry, baskets, and weaving. Also nearby are the White Sands National Monument (about 55 miles), the Carlsbad Caverns (about 160 miles), and Sierra Blanca, a 12,000 foot mountain with fine skiing (about 130 miles). The weather in early January is usually clear and sunny, with temperatures usually in the 50's in the daytime, and the 20's at night. Good skiing is one and a half hours away. Note: Full program will be mailed to all registrants in September and the preprints in December. Detailed accommodation and travel information will be sent on receipt of completed registration form. Hotel rates will be from $20-$50 per night. Since accommodation may be limited, to obtain hotel information, it is advisable to register early. ------------------------------ Date: Thu, 3 Jul 86 10:01:48 -0200 From: Moshe Vardi Subject: Conference - Database Theory 1986 - Program International Conference on Database Theory PROGRAM MONDAY, SEPTEMBER 8 Registration and coffee: 8:00am-10:30am Session 1. 10:30am-1:00pm. Chairperson: Giorgio Ausiello Database Queries and Programming Constructs (Invited Lecture), Ashok K. Chandra (IBM T.J. Watson Research Center, USA) Presentation of the Witold Lipski Award to V.S. Lakshmanan. Split-Freedom and MVD-Intersection: A New Characterization of Multivalued Dependencies Having Conflict-Free Covers, V. S. Lakshmanan (Indian Institute of Science, India) A Polynomial-time Join Dependency Implication Algorithm for Unary Multi-valued Dependencies, George Loizou (Birkbeck College, Univ. of London, UK), P. Thanisch (Lattice Logic, UK) Horizontal Decompositions Based on Functional-Dependency-Set- Implications, Paul De Bra (University of Antwerp UIA, Belgium) Luncheon: 1:00pm-2:30pm Session 2. 2:30pm-4:00pm. Chairperson: TBA Introduction to the Theory of Nested Transactions, Nancy A. Lynch (MIT, USA), Michael Merritt (ATT Bell Laboratories, USA) The Cost of Locking, Peter K. Rathmann (Stanford University, USA) Update Serializability in Locking R. C. Hansdah, L. M. Patnaik (Indian Institute of Science, India) Coffee Break: 4:00pm-4:30pm. Session 3. 4:30pm-6:00pm. Chairperson: John Mylopoulos. Restructuring of Semantic Database Objects and Office Forms, Serge Abiteboul (INRIA, France), Richard B. Hull (University of Southern California, USA) Entity-Relationship Consistency for Relational Schemas, Johann A. Makowsky, Victor M. Markowitz, N. Rotics (Technion, Israel) Unsolvable Problems Related to the View Integration Approach, Bernhard Convent (Universitaat Dortmund, Fed. Rep. of Germany) TUESDAY, SEPTEMBER 9 Session 4. 9:00am-10:45am. Chairperson: Domenico Sacca` Logic Programming and Parallel Complexity (Invited Lecture), Paris Kanellakis (Brown University, USA) Updating Logical Databases Containing Null Values, Marianne Winslett Wilkins (Stanford University, USA) Update Semantics under the Domain Closure Assumption, Laurence Cholvy (ONERA-CERT-DERI, France) Coffee Break: 10:45am-11:15am Session 5. 11:15am-12:45pm. Chairperson: Jan Paredaens On the Desirability of Gamma-Acyclic BCNF Database Schemes, Edward P.F. Chan, Hector J. Hernandez (University of Alberta, Canada) Set Containment Inference, Paolo Atzeni (IASI-CNR, Italy), D. Stott Parker (UCLA, USA) Interaction-Free Multivalued Dependency Sets, Dirk Van Gucht (Indiana University, USA) Luncheon: 12:45pm-2:30pm Session 6. 2:30pm-4:00pm. Chairperson: TBA Efficient Multidimensional Dynamic Hashing for Uniform and Non-Uniform Record Distributions, Hans-Peter Kriegel, Bernhard Seeger (Universitaat Wuerzburg, Fed. Rep. of Germany) List Organizing Strategies Using Stochastic Move-to-Front and Stochastic Move-to-Rear Operations, B. John Oommen (Carleton University, Canada), E. R. Hansen (Lockheed Missiles and Space Co., USA) Coffee Break: 3:30pm-4:00pm. Session 7. 4:00pm-5:30pm. Chairperson: TBA A Domain Theoretic Approach to Higher-Order Relations, Peter Buneman (University of Pennsylvania, USA) Theoretical Foundation of Algebraic Optimization Utilizing Unnormalized Relations, Marc H. Scholl (Technische Hochschule Darmstadt, Fed. Rep. of Germany) Modelling Large Bases of Categorized Data with Acyclic Schemes, F. M. Malvestuto (ENEA, Italy) Banquet: 8:00pm-11:00pm WEDNESDAY, SEPTEMBER 10 Session 8. 9:00am-10:45am. Chairperson: TBA The Generalized Counting Method for Recursive Logic Queries (Invited Lecture), Carlo Zaniolo (MCC, USA) Some Extensions to the Closed World Assumption in Databases, Shamim A. Naqvi (MCC, USA) Query Processing in Incomplete Logical Databases, Nadine Lerat (Universite` de Paris-Sud, France) Filtering Data Flow in Deductive Databases, Michael Kifer (SUNY at Stony Brook, USA), Eliezer L. Lozinskii (Hebrew University, Israel) Coffee Break: 11:15am-11:45am Session 9. 11:45am-12:45pm. Chairperson: TBA. A New Characterization of Distributed Deadlock in Databases, Ouri Wolfson (Technion, Israel) Towards Online Schedulers Based on Pre-Analysis Locking, Georg Lausen (Technische Hochschule Darmstadt, Fed. Rep. of Germany), Eljas Soisalon-Soininen (University of Helsinki, Finland), Peter Widmayer (Universitaat Karlsruhe, Fed. Rep. of Germany) PROGRAM COMMITTEE S.Abiteboul (France); G.Ausiello (Italy), chairman; F.Bancilhon (France, USA); A.D'Atri (Italy); M.Moscarini (Italy); J.Mylopoulos (Canada); J-M.Nicolas (France, West Germany); J.Nievergelt (Switzerland); C.H.Papadimitriou (Greece, USA); J.Paredaens (Belgium); D.Sacca` (Italy); N.Spyratos (France); J.D.Ullman (USA); M.Y.Vardi (USA). REGISTRATION Registration, except for students, includes technical sessions, one copy of the preprints of the proceedings, luncheons (Monday and Tuesday), banquet (Tuesday), and refreshments during the coffee breaks. Student registration is available to full-time students only, and must be documented by a faculty member certification or photocopy of student card, and includes the technical sessions, preprints and refreshments. Registration fee: Before Aug.15 After Aug.15 Member of IEEE or EATCS: Lit. 180000 [ ] 250000 [ ] US $ 120 [ ] 165 [ ] Nonmember: Lit. 200000 [ ] 270000 [ ] US $ 135 [ ] 180 [ ] Student: Lit. 75000 [ ] 100000 [ ] US $ 50 [ ] 65 [ ] [...] GENERAL INFORMATION LOCATION: Conference activities will take place in the headquarters of the Italian Research Council, in front of the main campus of the University of Rome "La Sapienza": CNR: Consiglio Nazionale delle Ricerche Piazzale Aldo Moro 7 MAIL AND MESSAGES: The official mailing address of ICDT'86 is: ICDT'86 c/o Paolo Atzeni IASI-CNR Viale Manzoni 30 00185 Roma Italy Telephone (before the conference) +39 (6) 770031 (during the conference) +39 (6) 4993379 Telex: 610076 CNRRM I (Attention: Dr. Atzeni IASI) During the conference, participants can receive mail at the above address, but are suggested to have telephone messages directed to the respective hotels. TRANSPORTATION: Aeroporto Leonardo Da Vinci, Fiumicino, is Rome International Airport. ACOTRAL buses leave the airport every 20 or 30 minutes for the downtown air terminal, located in Via Giolitti, at the main railway station (Stazione Termini). The hotels are within walking distance from the terminal (300mt). ACOTRAL costs Lit.6000 (about US $ 4.00), and tickets must be bought within the airport, before boarding the bus. Taxi fare from the airport to downtown is about Lit.45000 (about US $ 30) (authorized taxi cabs are yellow and have a license number; use only yellow taxis and ask for a receipt). Detailed information on how to get to the conference site (1500 mt. from the hotels) will be available at the hotels. BANQUET: The conference banquet will be held at Hotel Columbus, (Via della Conciliazione 33, near the Vatican). Vegetarian meals will be available only to preregistrants requesting them. Additional tickets for the banquet will be available at the registration desk for Lit.50000. TRAVEL INFORMATION: American Express offers various half-day tours of Rome every day, in the morning and in the afternoon, for about Lit. 30000-35000 (US $ 20 - 23), and one or two days tours to other interesting locations. Information requests to American Express can be sent together with hotel reservations. CLIMATE: Weather in Rome in September is quite warm, with temperatures between 25 and 30 degrees C (77 - 86 degrees F). THINGS TO SEE AND TO DO: Anything you like; the decision problem may be unsolvable. The organizers of ICDT'86 would like to thank the following financial supporters. - Banca Nazionale del Lavoro - Consiglio Nazionale delle Ricerche - Enidata S.p.A. - Selenia S.p.A. - Universita` di Roma "La Sapienza" ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jul 8 00:55:23 1986 Date: Tue, 8 Jul 86 00:55:18 edt From: vtcs1::in%<> (LAWS%SRI-AI.ARPA@SRI-STRIPE.ARPA) To: ailist@sri-ai.arpa Subject: AIList Digest V4 #162 Status: R AIList Digest Monday, 7 Jul 1986 Volume 4 : Issue 162 Today's Topics: Queries - Teaching CommonLisp & CPROLOG on VAX/VMS & Architectures for Interactive Systems, AI Tools - Scheme and CommonLisp Philosophy & Brain Theory - Representationalist Perception, Natural Language - References, Journals - AI Expert ---------------------------------------------------------------------- Date: Wed 2 Jul 86 09:40:53-PDT From: Mark Richer Subject: Teaching CommonLisp Lisp Teachers (or previous learners), I am interested in collecting comments regarding your experiences and preferences with texts for teaching/learning Lisp. The implementation available for the specific course I expect to be teaching is Golden CommonLisp on an IBM-PC, in case you want to factor that into your comments. You might want to think of this in the traditional way, which book(s) would you make required, highly recommended, or optional. Any other comments on teaching Lisp would be of interest. The students in this class will range from undergraduates that are novice programmers majoring in fields outside of CS, Math, or the sciences to CS majors and possibly graduate students. This course is not being taught in a Computer Science Department and little constraints have been placed on me. Hands-on lab sessions are possible as well as lectures. Mark ------------------------------ Date: 3 Jul 86 13:37:00 EST From: "CPT.GREG.ELDER" Reply-to: "CPT.GREG.ELDER" Subject: Help with CPROLOG on VAX/VMS Please excuse me if this is not the appropriate list for this message. I am looking for anyone running CPROLOG on a VAX under VMS 4.2. We have a problem when typing CONTROL-C under CPROLOG to enter the debug mode so as to be able to turn on tracing. If anyone has CPROLOG running successfully on a VAX under VMS 4.2, I would appreciate hearing from you. Thanks. Greg Elder ARPA: elder@wpafb-info1 CSNET: gelder@wright ------------------------------ Date: Thu, 3 Jul 86 18:03:11 edt From: brant%linc.cis.upenn.edu@CIS.UPENN.EDU Subject: Architectures for interactive systems? There seems to have been a great deal of work done in natural language processing, yet so far I am unaware of any attempt to build a practical yet theoretically well- founded interactive system or an architecture for one. When I use the phrase "practical yet theoretically well- founded interactive system," I mean a system that a user can interact with in natural language, that is capable of some useful subset of intelligent interactive (question- answering) behaviors, and that is not merely a clever hack. Many of the sub-problems have been studied at least once. Work has been done on various types of necessary response behavior, such as clarification and misconception correction. Work has been done on parsing, semantic interpretation, and text generation, and other problems as well. But has any work been done on putting all these ideas together in a "real" system? I see a lot of research that concludes with an implementation that solves only the stated problem, and nothing else. Presumably, a "real user" will not want to have to run system A to correct invalid plans, system B to answer direct questions, system C to handle questions with misconceptions, and so forth. I would be interested to get any references to work on such integrated systems. Also, what are people's opinions on this subject: are practical NLP too hard to build now? Should we leave the construction of practical systems to private enter- prise and restrict ourselves to the basic research problems? If we do so, how can we be sure we're actually making any contribution at all? Brant ==================== Brant Cheikes Department of Computer and Information Science University of Pennsylvania ARPA: brant@linc.cis.upenn.edu CSNET: brant%upenn-linc@upenn ------------------------------ Date: Wed 2 Jul 86 09:26:53-PDT From: Mark Richer Subject: Scheme and CommonLisp SCHEME and COMMONLISP ********************* On June 10th, 1986 I sent out a request for feedback on the language Scheme. In particular, I was interested in how appropriate the language would be for a large-scale development effort in ICAI versus Commonlisp. Implicit in this question are concerns about available implementations including development environments, efficiency, compactness, ease of learning, portability, etc. Below is a summary of comments. If you want to see the whole file of messages (13) I will send it to you upon request. Advantages of Scheme (compared to other Lisps including Commonlisp): ******************************************************************** Simple Consistent Small (easy to learn and can be implemented well on small, standard machines) Elegant Semantics of language are clean Closures and lexical scoping are handled well Migration to (i.e., learning) other dialects of Lisp should not be a problem Portable (but someone has to have implemented it on the target machine) Supports object-oriented programming and multiple processes For above reasons, it is very appropriate for learners, especially if the goal is to teach basic principles in computer science A net address to reach experts: SCHEME-TEAM%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU Advantages of Commonlisp ************************ Widely accepted standard Large, growing user community Lisp language development is concentrated on Commonlisp now Best programming environments do/will support Commonlisp Many built-in functions and features (overload beginner, but very useful) Portable (obvious reasons to expect good implementations, compilers, etc.) Commonlisp does require more memory than Scheme, but given the increasing availability of inexpensive large memories that issue might vanish. There is a Commonlisp mailing list, Common-Lisp@SU-AI.ARPA. I assume you need to contact Common-Lisp-Request@SU-AI.ARPA to get on the list, unless you have access to it through a local bboard. Other comments -------------- Scheme IS a dialect of Lisp, an UnCommonLisp though. Proust, an ICAI program, is implemented in T, a dialect of Scheme. Ableson and Sussman's "Structure and Interpretation of Computer Programs" (MIT Press, 1985) is highly recommended for everyone to read and is also suggested as a text to teach computer science (Scheme is the language used throughout the book). ------------------------------ Date: Wed 2 Jul 86 11:07:50-PDT From: Pat Hayes Subject: Representationalist Perception Mozes long review of Kelleys book "The Evidence of the Senses" tells one a lot about the book. In particular, it sounds as though it makes the same basic mistake about representations that many other 'anti-computationalist' philosophers , including Gibson and his followers, make. The 'representatonalist' account of perception does NOT claim that instead of perceiving the world, we perceive internal representations of the world. That would indeed be a position with many difficulties. Rather, it says that the WAY we perceive the world is BY making representations of it. The data structures are, to put it simply, the output of the perceptual process, not its input. The question the representational position must face is how such things ( representations ) can serve as percepts in the overall cognitive framework. While there are indeed many problems here, the position is not as silly as Gibson thought it was. Pat Hayes ------------------------------ Date: 1 Jul 86 14:08:00 PST From: sefai@nwc-143b.ARPA Reply-to: Subject: Natural Language References As promised, the following is a list of references on Natural Language. I'd like to thank all who contributed references as well as suggestions. Before I can definitely commit to my topic, I need to investigate work done by Harris and Wiley, Sager, and Winograd. Hopefully, I'll nail this down before summer's end. Will keep you posted. Gene Guglielmo SEFAI@NWC-143B China Lake, Ca. .rA Ananiashviii, G.G. .rA Mundzhishvii, Z.I. .rA Bichashvii, N.N. .rP Word Identification in a Natural Language in Interactive Systems .rC Soobshch. Akad. Nauk. Gurzin. SSR .rD 1984 .rA Boguraev, B.K. .rA Jones, K.S. .rP A Framework for Inference in Natural Language Front Ends to Databases .rI University of Cambridge Computer Laboratory .rC Report No. 64 .rD 1985 .rA Brachman, Ron (ed) .rA Levesque, Hector (ed) .rB Readings in Knowledge Representation .rI Morgan Kaufmann Publishers, Inc. .rW Palo Alto, California .rD 1986 .rA Briggs, R. .rP Transcendental Semantic Primitives for Natural Language Processing .rI Research Institute for Advanced Computer Science, NASA Ames Research Center .rC RIACS Techical Report TR 85.14 .rW Moffett Field, California .rD 1985 .rA Damerau, F.J. .rP An Interactive Customization Program for a Natural Language Database Query System .rI IBM Research Division .rC Report No. 10411 .rD 1984 .rA Damerau, F.J. .rP Problems and Some Solutions in Customization of Natural Language Data Base Front Ends .rI IBM Research Division .rC Report No. 10872 .rD 1984 .rA Dyer, M.G. .rB In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension .rI MIT Press .rW Cambridge, Massachusetts .rD 1986 .rA Enomoto, H. .rP TELL: a Natural Language Based Software Development System .rI Institute for New Generation Computer Technology .rC Report No. 67 .rD 1984 .rA Findler, Nicholas V. (ed) .rB Associative Networks: Representation and Use of Knowledge by Computers .rI Academic Press .rW NY .rD 1983 .rA Frederking, R.E. .rP Syntax and Semantics in natural Language Parsers .rI Carnegie-Melon University .rC Department of Computer Science .rC Report No. 85-133 .rD 1985 .rA Harris, M.D. .rB Introduction to Natural Language Processing .rA Harris, Z. .rA Wiley .rB A Grammar of English on Mathematical Principles .rD 1984 .rA Ibragimov, T.I. .rB Cybernetics and Natural Languages .rA Jacobs, P.S. .rP PHRED: A Generator for Natural Language Interfaces .rI University of California .rC Berkeley Computer Science Division .rC Report No. 85-198 .rD 1985 .rA Johnson, D.E. .rP Design of a Robust, Portable Natural Language Interface Grammar .rI IBM Research Division .rC Report NO. 10867 .rD 1984 .rA Johnson, T. .rB Natural Language Computing: The Commercial Applications .rI Ovum Limited .rW London .rA Kalita, J.K. .rP Generating Summary Responses to Natural Language Database .rI University of Saskatchewan .rC Report No. 84-9 .rD 1984 .rA Kandrirody, A. .rA Kapur, D. .rA Narendran, P. .rB An Ideal-Theoretic Approach to Word Problems and Unification Problems over Finitely Presented Commutative Algebras .rA Karpen, J.L .rP The Digitized Word: Orality, Literacy, and the Computerization of Language .rC Ph.D. thesis .rI Bowling Green State University .rW Bowling Green, Ohio .rD 1984 .rA Marcus, M.P. .rB A Theory of Syntactic Recognition for Natural Language .rI MIT Press .rW Cambridge, Massachusetts .rD 1985 .rA Mays, E. .rP A Modal Temporal Logic for Reasoning About Changing Database with Applications to Natural Language Question Answering .rI Unviersity of Pennsylvania .rC Moore School of Electrical Engineering .rC Department of Computer Science .rC Report No. 85-01 .rD 1985 .rA Michalski, R.S. .rA Carbonell, J.G. .rA Mitchell, T.M. .rB Machine Learning; An Artificial Intelligence Approach, Volume II .rI Morgan kaufman Publishers, Inc. .rW Palo Alto, California .rD 1986 .rA Neuamnn, B. .rP Natural Language Descriptions of TIme-Varying Scenes .rI Universitaet Hamburg. .rC Fachbereich Informatik .rC Report NO. 105 .rD 1984 .rA Orlowska, E. .rP The Montague Formalization of Natural Language .rI Polish Academy of Sciences .rC Institute of Computer Sciences .rC Report No. 105 .rD 1984 .rA Petrick, S.R. .rP Natural Language Database Query Systems .rI IBM Research Division .rC Report No. 10508 .rD 1984 .rA Rau, L.F. .rP The Understanding and Generation of Ellipses in a Natural Language Systems. .rI University of California Berkeley .rC Computer Science Division .rC Report No. 85-227 .rD 1984 .rA Sager, Naomi .rB Natural Language Information Processing .rI Addison-Wesley .rW Reading .rA Saint-Dizier, P. .rP An Approach to natural Language Semantics in Logic Programming .rI Institute National de Recherce en Informatique et en Automatique .rC Report NO. 389 .rA Salton .rA McGill .rB Introduction to Modern Information Retrieval .rA Schank, R.C (ed) .rA Colby, K.M. (ed) .rB Computer Models of Thought and Language .rI W.H.Freeman and Company .rW San Francisco .rD 1973 .rA Schank, R.C. .rB Conceptual Information Processing .rI Elsevier Science Publishers B.V. .rW Amsterdam .rD 1984 .rA Schank, R.C. .rA Childers, P.G. .rB The Cognitive Computer .rI Addison-Wesley .rW Reading .rD 1984 .rA Schieber, Stuart M. .rP An Introduction to Unification-based Approaches to Grammar .rI University of Chicago Press .rC CSLI Lecture Note Series .rD 1986 .rA Sowa, John F. .rB Conceptual Structures: Information Processing in Mind and Machine .rP Addison-Wesley .rW Reading .rD 1984 .rA VanRijsbergen .rB Information Retrieval, 2nd Edition .rA Winograd, Terry .rB Language as a Cognitive Process, Volume 1: Syntax .rI Addison-Wesley .rW Reading .rD 1983 .rP Large-Dictionary, On-Line Recognition of Spoken Words .rI Helsinki University of Technology .rC PB84-214246/CAO .rD 1983 .rB Natural Language Processing: A Knowledge Engineering Approach .rL 0-8476-7358-8 ------------------------------ Date: Sat 5 Jul 86 13:07:49-CDT From: CMP.BARC@R20.UTEXAS.EDU Subject: AI Expert Since the new "AI Expert" magazine was given such a glowing review, I thought the ensuing raft of potential subscribers might be interested that they can do a bit better than the $27 yearly subscription rate (which includes the premier and 12 other issues). Recent issues of its sister publication "Computer Language" include savings certificates that offer the 13-issue package for $22. Dallas Webster CMP.BARC@R20.UTexas.Edu ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Tue Jul 8 00:56:02 1986 Date: Tue, 8 Jul 86 00:55:56 edt From: vtcs1::in%<> (LAWS%SRI-AI.ARPA@SRI-STRIPE.ARPA) To: ailist@sri-ai Subject: AIList Digest V4 #163 Status: R AIList Digest Monday, 7 Jul 1986 Volume 4 : Issue 163 Today's Topics: AI Tools - The Logix System, Psychology - Psychnet BBoard, Games - Hitech Results, Techniques - Hopfield Networks for Traveling Salesman, Opinion - Common Sense, Philosophy - Creativity and Analogy ---------------------------------------------------------------------- Date: Thu, 3 Jul 86 17:03:11 -0200 From: Ehud Shapiro Subject: The Logix system We are pleased to announce the availability of the Logix system, an experimental Flat Concurrent Prolog program development environment. Logix can be used to study and experiment with concurrent logic programming, and to develop applications that can benefit from combining the expressive power of concurrency with that of the logical variable. Logix is not a conventional programming environment; although presently a single user single processor system, its basic design scales to a multiprocessor, multiuser system. With its novel approach to parallel computation control, its concept of active modules and its object-oriented design of system hierarchies, it is an interesting system to study in its own right. For the same reason it may be overdeveloped for the casual user in certain respects (e.g. its multitasking capabilities), and underdeveloped in others (e.g. interactive help, "friendliness"). Logix includes an FCP compiler to an abstract machine instruction set and a C emulator of the abstract machine. With the exception of the emulator and a few kernels, it is written entirely in Flat Concurrent Prolog. The system was bootstrapped in Summer 1985, and has seen extensive use and development since. It was used to develop applications (including Logix itself) whose total size is over 20,000 lines of FCP source code. Logix is available on Vax and Sun computers, under the Berkeley Unix and Ultrix operating systems. It is expected that applications developed under Logix would run almost directly on a multiprocessor implementation of Flat Concurrnt Prolog; the availability of such a prototype system for the Intel iPSC hypercube is announced separately. The handling fee for a non-commercial license to the Logix system is $250 U.S. To obtain a license form and/or a copy of the Logix user manual write to: Mr Yossef Dabby Department of Computer Science The Weizmann Institute of Science Rehovot 76100, Israel To obtain an electronic copy of the license write to: CSnet, Bitnet: logix-request@wisdom ARPAnet: logix-request%wisdom.bitnet@wiscvm.arpa References [1] A. Houri and E. Shapiro, "A sequential abstract machine for Flat Concurrent Prolog", Weizmann Institute Technical Report CS86-20, 1986. [2] W. Silverman, M. Hirsch, A. Houri, and E. Shapiro, "The Logix system user manual, Version 1.21", Weizmann Institute Technical Report CS86-21. [3] M. Hirsch, W. Silverman, E. Shapiro, "Layers of protection and control in the Logix system", Weizmann Institute Technical Report CS86-19, 1986. ------------------------------ Date: Mon, 30 Jun 86 12:34:27 CDT From: Robert C. Morecock Reply-to: EPSYNET@UHUPVM1 Subject: Announcement of new bboard named psychnet [Forwarded from Arpanet-BBoards by Laws@SRI-AI.] PSYCHNET (tm) Psychology Newsletter and Mailing List EPSYNET@UHUPVM1 The Psychnet mailing list and Newsletter sends out information and news to those who sign up. Within Bitnet, Psychnet is also a 24-hour server machine which mails out files to users who first send the PSYCHNET HELP command to userid UH-INFO at node UHUPVM1. OUTSIDE BITNET Psychnet is a mailing list and Newsletter only. Once per week ALL members receive the latest Psychnet Newsletter and Index of files available on the server machine. Outside Bitnet, if a file looks interesting send an E-mail request to userid EPSYNET (NOT uh-info) at node UHUPVM1 and the file will be shipped out to you. Persons within may also sign up for the mail list and will get the Newsletter and Index along with other news. Users within Bitnet should get their files directly from the server machine. An Exec file is available for CMS users and COM files are available for VAX users within Bitnet. If you have a file or idea you wish distributed to members of the list you may send it to userid EPSYNET at node UHUPVM1 and it will be sent out for you, usually with the week's Psychnet Newsletter. An initial formal purpose of Psychnet is distribution of academic papers in advance of this year's (1986) APA convention. Other purposes will develop according to the needs and interests of the profession and Psychnet users. All requests to be added to or deleted from the mailing list, or to have files distributed should be sent to: Coordinator: Robert C. Morecock, Psychnet Editor, EPSYNET@UHUPVM1 ------------------------------ Date: 6 Jul 86 22:37:15 EDT From: Murray.Campbell@k.cs.cmu.edu Subject: Hitech results [Forwarded from the CMU bboard by Laws@SRI-AI.] Hitech had a tough day, but set a new milestone for computer chess. In round 8, Hitech drew International Master Michael Rohde, rated 2602, for what we believe is the first draw by a computer against a titled player in regular tournament play. In round 9 Hitech lost to Hungarian Grandmaster Guyla Sax, rated 2769. Overall Hitech finished with 5.5/9, a respectable score given the quality of the competition. The performance rating was approximately 2440. ------------------------------ Date: Sat, 5 Jul 86 21:53:36 EDT From: ambar@EDDIE.MIT.EDU (Jean Marie Diaz) Reply-to: ambar@mit-eddie.UUCP (Jean Marie Diaz) Subject: Re: connectionism/complexity theory (an article published in the April 1, 1985 edition of Fortune--posted w/out permission) WHAT BELL LABORATORIES IS LEARNING FROM SLUGS [...] Inspired by the discoveries of physicist John Hopfield, a team of Bell Labs scientists has been using research on slugs' brains to develop a radically new type of computer. [...] The Bell computer does not always select the single [best traveling salesman] route, but--much like a human--it comes up with one of the better routes, and never picks anything obviously loony. New techniques for recording neurological activity in rats and in three types of slugs--favored because of their large and accessible nerve cells--are providing Bell's team with reams of information about how neurons work. But the conceptual focus of the Bell project is the model of the new neural-network computer created by Hopfield, 51, who splits his time between Bell Labs and the California Institute of Technology. Neural networks operate in the analog mode--when information enters the brain, the neurons start firing and their values, or "charges," rise and fall like electric voltage in analog computers. When information is digested, the network settles down into a so-called steady state, with each of its many neurons resting close to their highest or lowest values--effectively, then, either on or off. A computer designed to mimic a neural network would solve problems speedily by manipulating data in analog fashion. but it would report its findings when each neuron is either in the on or off state, operating like a digital computer speaking a binary language. The simulated computer designed by Hopfield and his AT&T colleagues uses microprocessors to do the work of neurons. Each microprocessor is connected to all others--as many neurons are interconnected--which would make the machine costly and complex to build. Another major difference between this computer and traditional ones is that memory is not localized in any one processor or set of processors. Instead, memory is in the patterns formed by all the neurons, whether on or off, when they are in steady states. As a result, the computer can deal with fragmentary or imprecise information. When given a misspelled name, for example, it can retreive the full name and data about the person by settling on the closest name in the network. Though analog computation is astonishingly fast, it sacrifices precision. Neural-network computers work best on problems that have more than one reasonable solution. Examples include airline scheduling, superfast processing for robots or weapons, and, more in AT&T's line, routing long-distance telephone traffic. -John Paul Newport -- AMBAR "I need something to change your mind...." ------------------------------ Date: 02 July 86 20:18 EDT From: KVQJ%CORNELLA.BITNET@ucbvax.Berkeley.EDU Subject: common sense I have been thinking a lot about the notion of common sense and its possible implementation into expert systems. Here are my ideas; I would appreciate your thoughts. Webster's Dictionary defines common sense as a 'practical knowledge'. I contend that all knowledge both informal and formal comes from this 'practical knowledge'. After all, if one thinks about Physics,Logic,or Chemistry,much of it makes practical sense in the real world. For example,a truck colliding with a Honda civic will cause more destruction than 2 Hondas colliding together. I think that people took this practical knowledge of the world and developed formal principles. It is common sense which distiguishes man from machine. If a bum on the street were to tell you that if you give him $5.00 he will make you a million dollars in a week, you would generally walk away and ignore him. If the same man were to input it into a so called intelligent machine,the machine would not know if he was Rockefeller or an indigent. My point is this, I think it is intrinically impossible to program common sense because a computer is not a man. A computer cannot experience what man can;it can not see or make ubiquitous judgements that man can. We may be able to program common-sense like rules into it,but this is not tantamount to real world common sense because real world common sense is drawn from a 'database' that could never be matched by a simulated one. Thank you for listening. sherry marcus kvqj@cornella ------------------------------ Date: Thu, 3 Jul 86 17:07 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Creativity and Analogy Jay Weber makes some interesting observations: > Consider the following view of analogy, consistent with its formal > treatment in many sources. A particular analogy, e.g. that which > exists between a battery and a reservoir, is a function that maps > from one category (set of instances) to another. Equivalently we > can view this function as a relation R between categories, in this > case we have a particular kind of "storage capability". This relation > is certainly > > 1) reflexive. "A battery is like a battery" (under any relation) > > 2) symmetric. "A battery is like a reservoir" implies > "A reservoir is like a battery" under the same relation R > > 3) transitive. "A battery is like a reservoir" and > "A reservoir is like a ketchup bottle" imply > "A battery is like a ketchup bottle" WHEN THE SAME > ANALOGY HOLDS BETWEEN THEM (same R). > > Then any analogy R is an equivalence relation, partitioning the space > of categories. Each analogy corresponds to a node in an abstraction > hierarchy which relates all of the sub-categories, SO THE SPACE OF > ANALOGIES MAPS ONTO THE SPACE OF ABSTRACTIONS, and so under these > definitions analogy and abstraction are equivalent. I agree with your reasoning and the conclusion that analogies map ONTO abstractions--in fact, I think they map ONTO and ONE-TO-ONE (in other words there is a one-to-one correspondence). Also, EACH analogy (and abstraction) partitions the space of categories into two subspaces. However, the SPACE of analogies does not partition the space of categories because the world can concurrently be modeled by multiple abstraction lattices (not necessarily hierarchies) in which the transitivity property may not hold. Consider the following: a) "A battery is like a reservoir" (storage capability) AND b) "A reservoir is like a pond" (body of water) DO NOT IMPLY: c) "A battery is like a pond" > ... > no one could agree to a particular formal definition of the term "analogy", > since we all have individual formal definitions by virtue of the fact that > we will answer yes or no when given a potential analogy instance, so we > are formal language acceptors with our senses as input. This is what I > mean by a "slippery" term, i.e. one that has drastically different > meanings depending on its user. This is why I say a formal definition > of analogy would satisfy very few people. I am glad that scientists, by and large, have not let "slipperiness" in some linguistic sense (as you define it) discourage them from carrying on their research. Of course, all research issues are "slippery" in a conceptual sense, by definition. (I would also expect a high degree of correlation between linguistic and conceptual "slipperiness"). There has been some discussion now (in AIList) on the relationship between "creativity" and "making-interesting-analogies". Is it mere empirical association or are there stronger causal links? One extreme view is that the definition of creativity is "making interesting analogies". Some recent illuminating discussions in this forum suggest that the ability to synthesize concepts from partial concepts in other domains is a key ingredient of a great number of creative activities. Is there some creative task that could not be performed by a machine capable of making complex analogies in an interesting manner--a complex analogy being defined as a many-to-one transformation between domains (as opposed to a simple analogy which is a one-to-one mapping)? Uttam Mukhopadhyay Computer Science Dept. General Motors Research Labs ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jul 10 06:46:26 1986 Date: Thu, 10 Jul 86 06:46:20 edt From: vtcs1::in%<> (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #164 Status: RO AIList Digest Thursday, 10 Jul 1986 Volume 4 : Issue 164 Today's Topics: Seminars - Mathematical Games (SU) & Discovery of Algorithms from Weak Methods (Rutgers) & The Koko Connection: Interspecies Communication (PARC) & Default Theories and Autoepistemic Logic (SRI), Conference - Expert Systems In Government ---------------------------------------------------------------------- Date: Tue 1 Jul 86 13:14:30-PDT From: Ilan Vardi Subject: Seminar - Mathematical Games (SU) [Forwarded from the Stanford bboard by Laws@SRI-AI.] The first meeting of the games seminar was quite a success with more than 20 people showing up.I'm hoping this will go on, so I've decided to lure people with FOOD to compete with various departmental teas. The subject this time around will be partizan games, which are games where opponents have different colours and have different moves available to them e.g. Go, chess etc. For people who weren't around last time the subject was IMPARTIAL games where both layers have the same alternatives. I showed that all those games can be reduced to one game called NIM which has a simple strategy explanable in five minutes. If you want to read up about thursday's talk, just pick up the copy of Knuth's "Surreal Numbers" that's on reserve at the Math Library. Remember that this meeting is at 3:00 p.m. room 381 T Math Department. Which is a CHANGE OF TIME from last week at 2:15 p.m.. If you have any comments, or want to get directly on a mailing list, just mail your answer here at zurdi@score. Have a nice day! Ilan Vardi ------------------------------ Date: 2 Jul 86 15:28:41 EDT From: Tom Fawcett Subject: Seminar - Discovery of Algorithms from Weak Methods (Rutgers) DISCOVERY OF ALGORITHMS FROM WEAK METHODS Armand E. Prieditis Weak problem-solving methods (e.g. means-ends analysis, breadth- first search, best-first search) all involve a search for some sequence of operators that will lead from an initial state to a goal state. This paper shows how it is possible to learn operators whose bodies contain algorithmic control constructs (e.g. loops, sequences, conditionals) such that the control construct itself applies the sequence needed to lead from the initial state to a goal state without a search for the sequence. By using explanation-based generalization [EBG] and an explicit theory of algorithms, the method learns operators (whose bodies contain algorithmic control constructs) that represent logically valid generalizations of the solution sequence. Where: Hill Center, Room 423 When: Tuesday, July 15th Speaker's EMail address: PRIEDITIS@RED.RUTGERS.EDU ------------------------------ Date: Mon, 7 Jul 86 10:36:11 PDT From: Hibbert.pa@Xerox.COM Reply-to: hibbert.pa@Xerox.COM Subject: Seminar - The Koko Connection: Interspecies Communication (PARC) PARC Forum Thursday, July 10, 1986 3:45PM, PARC Auditorium Mitzi Phillips Research Assistant and Lecturer, The Gorilla Foundation For 13 years the Gorilla Foundation has been dedicated to teaching American Sign langualtge to Koko, a 250-lb Lowland Gorilla. This talk shares the advances made in the field of interspecies communication. Through sharing personal experiences with Koko we will explore the valuable information learned about animal intelligence. This Forum is OPEN. All are invited. Host: Chris Hibbert (System Concepts Lab, 494-4382) Refreshments will be served at 3:30 pm Requests for videotaping should be sent to Susie Mulhern before Tuesday noon. Directions to PARC: The PARC Auditorum is located at 3333 Coyote Hill Rd. in Palo Alto. We are between Page Mill Road (west of Foothill Expressway) and Hillview Avenue, in the Stanford Research Park. The easiest way here is to get onto Page Mill Road, and turn onto Coyote Hill Road. As you drive up Coyote Hill, PARC is the only building on the left after you crest the hill. Park in the large parking lot, and enter the auditorium at the upper level of the building. (The auditorum entrance is located down the stairs and to the left of the main doors.) ------------------------------ Date: Wed 9 Jul 86 13:08:44-PDT From: Margaret Olender Subject: Seminar - Default Theories and Autoepistemic Logic (SRI) ON THE RELATION BETWEEN DEFAULT THEORIES AND AUTOEPISTEMIC LOGIC Kurt Konolige (KONOLIGE@SRI-AI) Artificial Intelligence Center SRI International and CSLI, Stanford University 11:00 AM, MONDAY, July 14 SRI International, Building E, Room EK228 Default theories are a formal means of reasoning about defaults: what normally is the case, in the absence of contradicting information. Autoepistemic theories, on the other hand, are meant to describe the consequences of reasoning about ignorance: what must be true if a certain fact is not known. Although the motivation and formal character of these systems are different, a closer analysis shows that they bear a common trait, which is the indexical nature of certain elements in the theory. In this paper we treat both autoepistemic and default theories as special cases of a more general indexical theory. The benefits of this analysis are that it gives a clear (and clearly intuitive) semantics to default theories, and combines the expressive power of default and autoepistemic logics in a single framework. VISITORS: Please arrive 5 minutes early so that you can be escorted up from the E-building receptionist's desk. Thanks! ------------------------------ Date: Wed, 2 Jul 86 10:30:06 edt From: camis..duke@mitre.ARPA Subject: Conference - Expert Systems In Government The Second Annual Expert Systems in Government Conference, sponsored by the Mitre Corporation and the IEEE Computer Society in association with the AIAA National Capital Section will be held October 20-24, 1986 at the Tyson's Westpark Hotel in McLean, VA. The tentative program, subject to changes and additions, is as follows: October 20-21 Tutorials Monday, October 20 Full Day Tutorial: Advanced Topics in Expert Systems by Kamran Parsaye, IntelligenceWare, Inc. Morning Tutorial: Knowledge Base Design for Rule Based Expert Systems by Casimir Kulikowski, Rutgers University Afternoon Tutorial: Knowledge Base Acquisition and Refinement by Casimir Kulikowski, Rutgers University Tuesday, October 21 Morning Tutorial: Distributed Artificial Intelligence by Kamal Karna, Computer Communications & Graphics Associates, Inc. and Barry Silverman, George Washington University Morning Tutorial: Introduction to Common Lisp by Carl Hewitt, MIT AI Lab Afternoon Tutorial: Lisp for Advanced Users by Carl Hewitt, MIT AI Lab Afternoon Tutorial: The Management of Expert System Development by Nancy Martin, Softpert Systems October 22-24 Technical Program Wednesday, October 22 9 - 10:30 Conference Chairman's Welcome Keynote Address: Douglas Lenat, MCC Program Agenda 11am - 12pm Track A: Military Applications I Bonasso, Benoit, et al.; An Experiment in Cooperating Expert Systems for Command and Control Major R. Bahnij, Major S. Cross; A Fighter Pilot's Intelligent Aide for Tactical Mission Planning G. Loberg, G. Powell Acquiring Expertise in Operational Planning: A Beginning Track B: Systems Engineering R. Entner, D. Tosh; Expert Systems Architecture for Battle Management H. Hertz; An Attribute Referenced Production System B. Silverman; Facility Advisor: A Distributed Expert System Testbed for Spacecraft Ground Facilities 12pm - 1pm Lunch, Distinguished Guest Address, The Honorable Charles Rose 1pm - 2:30pm Track A: Knowledge Acquisition I J. Boose, J. Bradshaw; NeoETS: Capturing Expert System Knowledge K. Kitto, J. Boose; Heuristics for Expertise Transfer M. Chignell; The Use of Ranking and Scaling in Knowledge Acquisition Track B: Expert Systems in the Nuclear Industry D. Sebo et al.; An Expert System for USNRC Emergency Response D. Corsberg; An Object-Oriented Alarm Filtering System J. Jenkins, W. Nelson; Expert Systems and Accident Management 3pm - 5pm Track A: Expert Systems Applications I R. Tong, et al.; An Object-Oriented System for Information Retrieval D. Niyogi, S. Srihari; A Knowledge-based System for Document Understanding R. France, E. Fox; Knowledge Representation in Coder Track B: Diagnosis and Fault Analysis M. Taie, S. Srihari; Device Modeling for Fault Diagnosis Z. Xiang, S. Srihari; Diagnosis Using Multi-level Reasoning B. Dixon; A Lisp-Based Fault Tree Development Environment Panel Track: 1pm - 5pm Management of Uncertainty in Expert Systems Chair: Ronald Yager, IONA College Participants: Lofte Zadeh, UC Berkeley Piero Bonissone, G.E. Laveen Kanal, University of Maryland Thursday, October 23 9am - 10:30am Track A: Parallel Architectures L. Sokol, D. Briscoe; Object-Oriented Simulation on a Shared Memory Parallel Architecture H. Sowizral; A Basis for Distributed Blackboards J. Gilmer; Parallelism Issues in the CORBAN C2I Representation Track B: Aerospace Applications of Expert Systems J. Popolizio, J. Feinstein; Space Station Security: An Expert Systems Approach D. Zoch; A Real-time Production System for Telemetry Analysis J. Schuetzle; A Mission Operations Planning Assistant P. Roach, D. Brauer; Ada Knowledge Based Systems F. Rook, T. Rubin; An Expert System for Conducting a Sattelite Stationkeeping Maneuver Panel Track: Star Wars and AI; Chair: John Quilty, Mitre Corp. 11am - 12pm Plenary Address: B. Chandrasekaran; The Future of Knowledge Acquisition 12pm - 1pm Lunch 1pm - 2:30pm Track A: Inexact and Statistical Measures K. Lecot; Logic Programs with Uncertainties N. Lee; Fuzzy Inference Engines in Prolog/P-Shell J. Blumberg; Statistical Entropy as a Measure of Diagnostic Uncertainty Track B: High Level Tools for Expert Systems S. Shum, J.Davis; Use of CSRL for Diagnostic Expert Systems E. Dudzinski, J. Brink; CSRL: From Laboratory to Industry D. Herman, J. Josephson, R. Hartung; Use of the DSPL for the Design of a Mission Planning Assistant J. Josephson, B. Punch, M. Tanner; PEIRCE: Design Considerations for a Tool for Abductive Assembly for Best Explanation Panel Track: Application of AI in Telecommunications Chair: Shri Goyal, GTE Labs Participants: Susan Conary, Clarkson University Richard Gilbert, IBM Watson Research Center Raymond Hanson, Telenet Communications Edward Walker, BBN Richard Wolfe, ATT Bell Labs 3pm - 5pm Track A: Expert System Implementations S. Post; Simultaneous Evaluation of Rules to Find Most Likely Solutions L. Fu; An Implementation of an Expert System that Learns R. Frail, R. Freedman; OPGEN Revisited Track B: Expert System Applications II R. Holt; An Expert System for Finite Element Modeling A. Courtemanche; A Rule-based System for Sonar Data Analysis F. Merrem; A Weather Forecasting Expert System R. Ahad, A. Basu; Explanation in an Expert System W. Vera, R. Bozolcz; AI Techniques Applied to Claims Processing Panel Track: Command and Control Expert Systems Chair: Andrew Sage, George Mason University Participants: Peter Bonasso, Mitre Stephen Andriole, International Information Systems Paul Lehner, PAR Leonard Adelman, PAR Walter Beam, George Mason University Jude Franklin, PRC Friday, October 24 9am - 12pm: Classified Track Classified Working Session: The community building expert systems for classified applications is unsure of the value and feasibility of some form of communication within the community. This will be a session consisting of discussions and working sessions, as appropriate, to explore these issues in some depth for the first time, and to make recommendations for future directions for the classified community. 9am - 10:30am Track A: Military Applications K. Michels, J. Burger; Missile and Space Mission Determination J. Baylog; An Intelligent System for Underwater Tracking J. Neal et al.; An Expert Advisor on Tactical Support Jammer Configuration Track B: Expert Systems in the Software Lifecycle D. Rolston; An Expert System for Reducing Software Maintenance Costs M. Rousseau, M. Kutzik; A Software Acquisition Consultant R. Hobbs, P. Gorman; Extraction of Data System Requirements Panel Track: Next Generation Expert System Shells Chair: Art Murray, George Washington University Participants: Joseph Fox, Software A&E Barry Silverman, George Washington University Lee Erman, Teknowledge Chuck Williams, Inference John Lewis, Martin Marietta Research Labs 11am - 12pm Track A: Spacecraft Applications D. Rosenthal; Transformation of Scientific Objectives into Spacecraft Activities M. Hamilton et al.; A Spacecraft Control Anomaly Resolution Expert System Track B: Knowledge Acquistion and Applications E. Tello; DIPOLE - An Integrated AI Architecture H. Chung; Experimental Evaluation of Knowledge Acquisition Methods Panel Track: Government Funding of Expert Systems Chair: Commander Allen Sears, DARPA Conference Chairman: Kamal Karna Unclassified Program Chairman: Kamran Parsaye Classified Program Chairman: Richard Martin Panels Chairman: Barry Silverman Tutorials Chairman: Steven Oxman Registration information can be requested from IEEE Computer Society Administrative Office 1730 Massachusetts Ave. N.W. Washington, D.C. 20036-1903 (202) 371-0101 ------------------------------ End of AIList Digest ******************** From vtcs1::in%<> Thu Jul 10 06:46:39 1986 Date: Thu, 10 Jul 86 06:46:35 edt From: vtcs1::in%<> (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #165 Status: RO AIList Digest Thursday, 10 Jul 1986 Volume 4 : Issue 165 Today's Topics: Books - Lisp Texts, Natural Language - Integrated Systems, AI Tools - VAX LISP Sources, Theory - Intelligence Tests & Analogy & Common Sense & Representationalist Perception ---------------------------------------------------------------------- Date: Tue, 8 Jul 86 13:08 EST From: HAFNER%northeastern.edu@CSNET-RELAY.ARPA Subject: Lisp texts Replying to Mark Richer's query about texts for teaching Lisp: There are a number of good textbooks on Lisp. I prefer Winston & Horn because of the emphasis on applications of Lisp, especially to AI. However, whatever text you choose, you should supplement it with "The Little Lisper" 2nd edition by Dan Friedman and Matthias Felleisen. TLL is a wonderful teaching tool - it is skill-oriented, thorough, and entertaining. I expect it will be especially useful for the students who are not math or CS majors. Good luck!! Carole Hafner hafner@northeastern P.S. Regarding the appropriateness of comments on Lisp programming on the AILIST: I find this material interesting, relevant, and highly appropriate. Lisp is the medium for most AI research, and effective use of that medium is of great concern to many. Ditto for other programming methods (logic programming, object oriented programming, etc.) ------------------------------ Date: Tue, 8 Jul 86 09:09:13 edt From: Eric Nyberg Subject: Re: Architectures for interactive systems? > There seems to have been a great deal of work done in > natural language processing, yet so far I am unaware of > any attempt to build a practical yet theoretically well- > founded interactive system or an architecture for one. ... > Many of the sub-problems have been studied at least once. > Work has been done on various types of necessary response > behavior, such as clarification and misconception correction. > Work has been done on parsing, semantic interpretation, and > text generation, and other problems as well. But has any > work been done on putting all these ideas together in a > "real" system? ... > I would be interested to get any references to work on such > integrated systems. Also, what are people's opinions on this > subject: are practical NLP too hard to build now? > Brant Cheikes I am part of a research project that has been investigating integrated architectures for intelligent interfaces at GTE Laboratories. A good overview of our recent work can be found in the Summer issue of IEEE Expert, in a paper entitled "An Intelligent Database Assistant" [Jakobson 86]. The phrase "practical yet theoretically well-founded" strikes at one of the basic difficulties in building a natural language interface as part of a working system - it should work in a reasonable amount of time, yet be as flexible as possible in the different kinds of utterances it can understand. The two extremes are seen in a keyword-based system, where parsing is done by a hand-coded program, versus a formally complete English grammar system, where parsing is done by a large, complex data structure (e.g., an ATN). The simplifying requirement we have placed on our applications is quite similar to the desire for a narrow, well-defined domain in building expert systems. If the domain of application for the intelligent interface is well-defined, and fairly narrow, a semantic grammar approach can be used quite successfully to provide good performance with reasonably complete coverage. The semantic grammar approach that we use is based on case theory, a linguistic paradigm that was investigated in the late sixties and early seventies (for a good summary of case- based approaches, see [Bruce 75]). The case-frame approach to parsing natural language has also been researched by Jaime Carbonell, Phil Hayes [Hayes 85], and others at CMU. Case frame parsing forms the basis for the Language Craft product offered by Carnegie Group. Of course, there are some drawbacks to the approach, most notably a somewhat informal, arbitrary definition of syntax, which makes the case-frame approach less satisfying from a theoretical linguistic viewpoint. However, some of the more complex syntactic constructions (like relative clauses) seem to be less important in this kind of system than discourse phenomena like ellipsis and anaphora. The dialog our system has with a user is very task oriented, and generally does not require the more complex constructions of unrestricted English prose. In my opinion, "practical" and "theoretically well-founded" are two qualities that a natural language system can have, and for each potential application, the proper mix of efficiency and coverage must be found. -- Eric Nyberg References ---------- [Bruce 75] Bruce, B., "Case Systems for Natural Language," Artificial Intelligence, Vol. 6, No. 4, April 1975, pp. 327-360. [Hayes 85] Hayes, P., et. al., "Semantic Caseframe Parsing and Syntactic Generality," Proc. 23rd ACL, Jul. 1985, pp. 153-160. [Jakobson 86] Jakobson, G., et. al., "An Intelligent Database Assistant," IEEE Expert, Vol. 1, No. 2, Summer 1986, pp. 65-78. {other references to intelligent interfaces can be found in the bibliography of [Jakobson 86]} ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CSNET: ehn0@gte-labs Eric H. Nyberg, 3rd UUCP: ..harvard!bunny!ehn0 GTE Laboratories, Dept. 317 ARPA: ehn0%gte-labs@csnet-relay 40 Sylvan Rd. Waltham, MA 02254 (617) 466-2518 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ------------------------------ Date: Wed, 9 Jul 86 16:55:44 pdt From: saber!matt@SUN.COM (Matt Perez) Subject: Re: Architectures for interactive systems? > I would be interested to get any references to work on such > integrated systems. Sorry, I have only a vague reference (see below), but I do have a couple of comments. > Also, what are people's opinions on this > subject: are practical NLP too hard to build now? I don't think it is impossible to integrate such a system. For example, the *Unix Consultant* at UCB is such an integrated system, albeit for research rather than commercial purposes. But its application is practical enough: to provide an on-line Unix expert which can communicate with the user in natural language, for input as well as in its responses. > Should we > leave the construction of practical systems to private enter- > prise and restrict ourselves to the basic research problems? Lord, NOOOOOOOOOOOO. The integration work is just beginning and I suspect it is a lot more complicated than taking care of the individual subproblems. I'd say that "the construction of practical systems" IS a basic research problem. All that private enterprise can afford to do is implement what works, and as you well pointed out, ain't much that works so far. As an alternative, I offer that Natural Language by itself is not that natural a way to communicate anyways. In many instances a Graphical Interface is much more appropriate. Of course, by Natural Language I mean written language or even speech; by Graphical Interface I mean Graphics (generative and otherwise) display and feedback and input devices that exploit our kinetic abilities. Thus I rather point at a feature in a good display than describe the same feature verbally. If you don't agree with me on that, try to describe a scene to someone over the phone. In other instances, formulae is the communications tool of excellence. It depends. Ideally, I say, the user interface should support all of the above! Basically, however, I agree with you in the following way: let's first learn to build systems (and enumerate architectures) that support (solely) a Natural Language interface. Ditto for graphics. Ditto for formulae. Then, let's see if we can take the best of each and put them together reliably and appropriately. And if that ain't basic research ... * Matt Perez * DISCLAIMER: beis-ball has bean bery, bery guud too me matt@saber.uucp sun!saber!matt@decwrl.dec.com ...{ihnp4,sun}!saber!matt Saber Technology Corp / 2381 Bering Drive / San Jose, CA 95131 (480) 435-8600 ------------------------------ Date: Mon, 7 Jul 86 22:51:19 edt From: beer%case.csnet@CSNET-RELAY.ARPA Subject: VAX LISP Sources In a previous AIList (Vol. 4, Issue 127), I posted a message concerning the availability of a set of tools and utilities for VAX LISP. At that time, only the object code was in the public domain. However, by popular request, we have arranged to make the source code for these facilities available. Anyone who requested a tape of the object code will be sent the source. The description of the facilities is repeated below. Here at the Center for Automation and Intelligent Systems Research at Case Western Reserve University, we have developed a number of tools and utilities for VAX LISP. They include extensions to the control and string manipulation primitives, a simple pattern matcher, a pattern-based APROPOS facility, a pattern-based top-level history mechanism, an extensible top-level command facility, an extensible DESCRIBE facility, and an implementation of Flavors. These facilities are described in detail in a technical report, "CAISR VAX LISP Tools and Utilities" (TR-106-86). A tape containing the VAX LISP source for these facilities is available for a $35 shipping and handling fee. Randall D. Beer (beer%case@CSNet-Relay.ARPA) Center for Automation and Intelligent Systems Research Case Western Reserve University Glennan Bldg., Room 312 Cleveland, OH 44106 ------------------------------ Date: 7 Jul 1986 1059-PDT (Monday) From: Eugene miya Subject: A comment to an interesting posting to net.ai <"Expert systems" are not AI.> The following appeared on the USENET's net.ai list (distinct from the mod.ai list gateway to the ARPAnet. My commentary follows: >From: michaelm@bcsaic.UUCP (michael maxwell) >Subject: Re: The Turing-Ring Test -- A Limitation Game. >Message-ID: <589@bcsaic.UUCP> >Date: 3 Jul 86 17:14:26 GMT > >In article <7101.8606281319@maths.qmc.ac.uk> gcj@qmc-ori.UUCP (The Joka): >>The following test has been proposed. Appoint one (or more) >>adjudicators to decide on which of the two parties in the >>test, persons A and B, is talking to a telephone answering >>machine and which is talking to a human being. This test is >>not limited to textual information, although person A should >>relay the same information as person B. > >Wonderful idea! An even better idea: You've probably answered the phone, >only to find that the voice on the other end is a computerized "survey". I >propose the following test: which of two computerized "survey" >programs is talking to a telephone answering machine and which is talking to a >human being...:-) >-- >Mike Maxwell >Boeing Artificial Intelligence Center > ...uw-beaver!uw-june!bcsaic!michaelm I have been thinking about the characteristics of a real Turing test. Here are some thoughts and some questions. 1) The Turing test is basically a psychological test of "discrimination" [a loaded word in our society today]. 2) given that the task is to create a machine "with intelligence," a) how long should such a test be? b) what is the shortest `length' of such a test? 3) Since the objective is whether a machine is intelligent or not (as opposed to `how' intelligent, i.e. an `intelligence test'), how should the test be composed? It seems that it can be made a signal detection task, and if so, it will have the standard concepts of false-positives and true-negatives (all that stuff from radar). It seems that such a test would be composed of rather difficult questions of the type: "Your wife (husband) and your daughter (son)have fallen into the water. You are positioned in the middle and can only save one. Who do you save?" Single difficult questions are probably insufficient. Are aggregate questions any better? Humans are bound to `fail' many questions. Such questions would be great for a conference to be held in say 2000 when the 50th anniversery of Turing's original paper was published. >From the Rock of Ages Home for Retired Hackers: --eugene miya NASA Ames Research Center eugene@ames-aurora.ARPA "You trust the `reply' command with all those different mailers out there?" {hplabs,hao,dual,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene [Sounds like the test for androids in Blade Runner. The problem of discriminating between two classes of intelligence is much easier than that of discriminating intelligence from all possible forms of nonintelligence. By the way, the fastest way to identify human intelligence may be to look for questions that a human will recognize as nonsense or outside his expected sphere of knowledge ("How long would you broil a 1-pound docket?" "Is the Des Moines courthouse taller or shorter than the Wichita city hall?") but that an imitator might try to bluff through. -- KIL] ------------------------------ Date: Tue, 8 Jul 86 17:47:02 edt From: Jay Weber Reply-to: jay@rochester.UUCP (Jay Weber) Subject: Transitivity of a *particular* analogy, and let's do science! In repsonse to my claim that particular analogies are transitive, Uttam Mukhopadhyay writes: >However, the SPACE of analogies does not partition the space of >categories because the world can concurrently be modeled by multiple >abstraction lattices (not necessarily hierarchies) in which the >transitivity property may not hold. Consider the following: > > a) "A battery is like a reservoir" (storage capability) > AND b) "A reservoir is like a pond" (body of water) > >DO NOT IMPLY: > c) "A battery is like a pond" But I orginally wrote: >> 3) transitive. "A battery is like a reservoir" and >> "A reservoir is like a ketchup bottle" imply >> "A battery is like a ketchup bottle" WHEN THE SAME >> ANALOGY HOLDS BETWEEN THEM (same R). Note the use of "SAME ANALOGY" which is not the same as "any analogy" as is the basis of Uttam's example above. Of course, any two categories are analogous with respect to some mapping function, so the relation "is analogous to" is vacuous. This distinction tends to be obscured by the fact that most linguistic examples of analogy (like those above) leave the mapping function implicit. Furthermore, I did not claim that the SPACE of analogies partitions the space of categories, but that a particular analogy does: >> Then any analogy R is an equivalence relation, partitioning the space >> of categories. I also questioned the value of asking whether "creativity" is equivalent to "making interesting analogies" to which Uttam replied: > I am glad that scientists, by and large, have not let "slipperiness" in >some linguistic sense (as you define it) discourage them from carrying on >their research. Proper scientists (by definition) do not construct theories about things that cannot be empirically examined, e.g. using structure mapping functions to model the communal descriptive definition of the English word "creativity". Scientists pick testable domains such as problem solving where you can test predictions of a particular theory with respect to correct problem solving. In the past, scientists have left debate over such concepts as "truth" and "beauty" to philosophers, and I think we should do the same with "creativity" and "intelligence". In Cognitive Science, researchers have too often exaggerated the impact of their work through the careless and unscientific use of such terms. Jay Weber Computer Science Department University of Rochester Rochester, NY 14627 jay@rochester ------------------------------ Date: 8 Jul 86 17:30 PDT From: Newman.pasa@Xerox.COM Subject: Re: Common Sense Philosophically, Sherry Marcus' ideas about common sense are poor in the same sense that I think Searle and Dreyfus' ideas about why AI won't ever happen are poor. As near as I can tell all three end up with some feature of human intelligence which cannot be automated for basically unexplained reasons. Marcus' problem is simpler than the others (why can't a computer have a real world common sense database like a human's?), but it is the same basic philosophical trap. All three appear to believe that there is some magical property of human intelligence (Searle and Dreyfus appear to believe that there is something special about the biological nature of human intelligence) which cannot be automated, but none can come up with a reason for why this is so. Comments?? I would particularly like to hear what you think Searle or Dreyfus would say to this. >>Dave ------------------------------ Date: Wed, 9 Jul 86 09:18:47 -0200 From: Eyal mozes Subject: Re: Representationalist Perception > The > 'representatonalist' account of perception does NOT claim that instead of > perceiving the world, we perceive internal representations of the world. > That would indeed be a position with many difficulties. Rather, it says > that the WAY we perceive the world is BY making representations of it. > The data structures are, to put it simply, the output of the perceptual > process, not its input. I would agree with Gibson (and with Kelley) that this boils down to the same thing. The "output" of perception (if such a term is appropriate) is our awareness. Realists claim that this awareness is directly of external objects. Representationalists, on the other hand, claim that we are directly aware only of internal representations, created by a process whose input are external objects; this means that we are aware of external objects only INDIRECTLY. That is the position Gibson and Kelley argue against, and I think they do understand it accurately. Note that the above applies only to PERCEPTUAL representationalists. It does not apply to COGNITIVE representationalists, who may agree that perception is direct, but claim that internal representations are then formed for the purpose of conceptual thinking. Gibson claimed that concept-formation is direct as well; but on this point, Kelley disagrees with him (this is indicated by his discussion of the issue in chapter 7 of "The Evidence of the Senses"; by his paper "A Theory of Abstraction", published in "Cognition and Brain Theory", vol. 7, no. 3 and 4, Summer/Fall 1984; and by his references to Ayn Rand's "Introduction to Objectivist Epistemology"). Eyal Mozes BITNET: eyal@wisdom CSNET and ARPA: eyal%wisdom.bitnet@wiscvm.ARPA UUCP: ..!ucbvax!eyal%wisdom.bitnet ------------------------------ End of AIList Digest ******************** From csnet_gateway Mon Jul 14 22:41:47 1986 Date: Mon, 14 Jul 86 22:41:42 edt From: csnet_gateway (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #166 Status: RO AIList Digest Monday, 14 Jul 1986 Volume 4 : Issue 166 Today's Topics: Philosophy - Representationalist Perception & Searle's Chinese Room ---------------------------------------------------------------------- Date: Fri, 11 Jul 86 17:03:37 edt From: David Sher Reply-to: sher@rochester.UUCP (David Sher) Subject: Re: Representationalist Perception In article <8607100457.AA12123@ucbvax.Berkeley.EDU> eyal@wisdom.BITNET (Eyal mozes) writes: >The "output" of perception (if such a term is appropriate) is our >awareness. Realists claim that this awareness is directly of external >objects. Representationalists, on the other hand, claim that we are >directly aware only of internal representations, created by a process >whose input are external objects; this means that we are aware of >external objects only INDIRECTLY. That is the position Gibson and >Kelley argue against, and I think they do understand it accurately. I may be confused by this argument but as far as visual perception is concerned we are certainly not aware of the firing rates of our individual neurons. We are not even aware of the true wavelengths of the light that hits our eyes. We have special algorithms built into our visual hardware that implements an algorithm that decides based on global phenomena the color of the light in the room and automatically adjusts the colors of percieved objects to compensate (this is called color constancy). However this mechanism can be fooled. Given that we don't directly percieve the lightwaves hitting our eyes how can we be directly percieving objects in the world? Does percieve in this sense mean something different from the way I am using it? I know that for ordinary people the only images consciously accessible are quite heavily processed to compensate for noise and light intensity and to take into account known facts about the tendencies of objects to be continuous and to fit into know shapes. I don't know how under such circumstances we can be said to be directly aware of any form of visual input except internal representations. My guess is that you are using words in a technical way that has confused me. But perhaps you can clear up this. ------------------------------ Date: Mon 14 Jul 86 10:09:34-PDT From: Stephen Barnard Subject: perception (realist vs. representationalist position) Maybe I've never really understood the arguments of the so-called "perceptual realists" (Gibson, etc.), because their position that we do not build internal representations of the objects of perception, but rather perceive the world directly (whatever that means), seems obviously wrong. Consider what happens when we look at a realistic painting. We can, at one level, see it as a painting, or we can see it as a scene with no objective existence whatsoever. How could this perception possibly be interpreted as anything but an internal representation? In many or perhaps even all situations, the stimuli available to our sense organs are insufficient to specify unique external objects. The job of perception, as opposed to mere sensation, is to complement the stimulus information to create a fleshed-out interpretation that is consistent both with the stimulus and with our knowledge and expectations. Gibson emphasized the richness of the visual stimulus, arguing that much more information was available from it than was generally realized. But to go from this observation to the conclusion that the stimulus is in all cases sufficient for perception is clearly not justified. ------------------------------ Date: Fri, 11 Jul 86 15:33:04 edt From: Tom Scott Subject: Knowledge is structured in consciousness Two recent postings to this newsgroup by Eyal Mozes and Pat Hayes on the (re)presentation of perception and knowledge in integrated sensory/knowledge systems indicate the validity of philosophy in the theoretical foundations of knowledge science, which includes AI and knowledge engineering. I'd prefer not to make a public choice between Mozes' vs. Hayes' position, but I'm impressed by the sincerity of their arguments and the way each connects philosophy and technology. Hayes remarks that "The question the representational position must face is how such things (representations) can serve as percepts in the overall cognitive framework." This is indeed a serious problem facing the designers of fifth- and sixth-generation intelligent systems. Here is a two-hundred-year-old approach to the problem, an approach that not only can help the representationalists but can also be of value to realist and idealist (re)constructions of knowledge within the simulated consciousness of a knowledge system: REPRESENTATION | +---------------+-------------+ | | UNCONSCIOUS CONSCIOUS REPRESENTATION REPRESENTATION (AI/KE) (Perception) | | +------------------+ +------+--------+ | | | | | RULE FRAME LOGIC OBJECTIVE SUBJECTIVE BASED BASED BASED PERCEPTION PERCEPTION (Knowledge) (Sensation) | +------------------+ Refers to the Relates | | object by means immediately to <-- INTUITION CONCEPT --> of a feature the object | which several +-------------+ things have in | | common Has its origin in PURE EMPIRICAL the understanding alone <-- CONCEPT CONCEPT (not in sensibility) (Notion) | A concept of reason <-- IDEA formed from notions and therefore transcending the possibility of experience This taxonomy tree of mental (re)presentations in a knowledge system was drawn by Jon Cunnyngham of Genan Intelligent Systems (Columbus, Ohio) after a group discussion on the following passage from Kant's "Critique of Pure Reason" (B376-77): The genus is representation in general (repraesentatio). Subordinate to it stands representation with consciousness (perceptio). A perception which relates solely to the subject as the modification of its state is sensation (sensatio), an objective perception is knowledge (cognitio). This is either intuition or concept (intuitus vel conceptus). The former relates immediately to the object and is single, the latter refers to it mediately by means of a feature which several things may have in common. The concept is either an empirical or a pure concept. The pure concept, in so far as it has its origin in the understanding alone (not in the pure image of sensibility), is called a notion. A concept formed from notions and transcending the possibility of experience is an idea or concept of reason. Anyone who has familiarised himself with these distinctions must find it intolerable to hear the representation of the colour, red, called an idea. It ought not even to be called a concept of understanding, a notion. A word of caution about the translation: First, the German "Anschauung" is translated into English as "intuition." Contrary to what my wife would have you think, this word should not be taken in the sense of "woman's intuition" but rather in the sense of "raw intake" or "input." Second, although "Einbildung" comes over to English naturally as "image," the imaging faculty ("Einbildungskraft") should only with caution be designated in English by "imagination," especially when we consider that the transcendental role of this faculty is the central organizing factor in Kant's theory of the human(oid) knowledge system. Third, the Norman Kemp Smith edition, available through St. Martin's Press in paperback for somewhere in the neighborhood of $15.00, is the best English translation, despite the little problems I've just pointed out regarding "Anschauung" and "Einbildung." The other translations pale in comparison to Smith's. In view of all this, I'd like to add to Hayes's challenge: Yes, there is a problem in the integration of perceptual (or should we say "sense-based") and intellectual systems. But the solution is already indicated in Kant's reconstruction of the human(oid) knowledge system by the equating of "objective perception," "knowledge," and "cognitio" (which, by the way, may or may not be equivalent to the English use of "cognition"). The problem can be pinpointed more exactly in this way: How can we force the system's objects to obey the apriori structures of consciousness that are necessary for empirical consciousness (awareness) of intelligible objects in a world, given to a self. (The construct of a self in a sense-based system of objective knowledge may seem to be a luxury, but without a self there can be no object, hence no objective perception, hence no knowledge.) What do we have now? Do we have intelligent systems? Perhaps. Do we have knowledgeable systems? Maybe. Are they conscious? No. The Hauptsatz for knowledge science is this: "Knowledge is structured in consciousness." So investigate consciousness and the self in the human, and then you'll have a basis for (re)constructing it in a computerized knowledge system. One more diagram that may be of help in unravelling all this: Understanding Sensibility | E Knowledge Images m of --------> Objects p objects | | ----------------------+----------------------- T | r Pure concepts Schemas Pure forms of a (categories) --------> intuition n and principles | (space and time) s | As was mentioned in an earlier posting to this newsgroup (V4 #157), this diagram springs from a single sentence in the Critique (B74): "Beide sind entweder rein, oder empirisch" (Both may be either pure [transcendental] or empirical). May I suggest that knowledge-system designers consider the diagram in conjunction with the taxonomy tree of mental representations. With these two diagrams in mind, two seminal passages from the Critique (namely, B33-36 and B74-79) can now be recognized for what they are: the basis for the design of integrated sense/knowledge systems in the fifth and sixth generations. To be sure, there is a lot of work to be done, but it can be done in a more holistic way if the Critique is read as a design manual. Tom Scott CSNET: scott@bgsu Dept. of Math. & Stat. ARPANET: scott%bgsu@csnet-relay Bowling Green State Univ. UUCP: cbosgd!osu-eddie!bgsuvax!scott Bowling Green OH 43403-0221 ATT: 419-372-2636 (work) ------------------------------ Date: Sun, 13 Jul 86 23:16:27 PDT From: kube%cogsci@berkeley.edu (Paul Kube) Subject: Re: common sense >From Newman.pasa@Xerox.COM, AIList Digest V4 #165: >...All three appear >to believe that there is some magical property of human intelligence >(Searle and Dreyfus appear to believe that there is something special >about the biological nature of human intelligence) which cannot be >automated, but none can come up with a reason for why this is so. > >Comments?? I would particularly like to hear what you think Searle or >Dreyfus would say to this. Searle and Dreyfus agree that human intelligence is biological (and so *not* magical), and in fact believe that artificial intelligences probably can be created. What they doubt is that a class of currently popular techniques for attempting to produce artificial intelligence will succeed. Beyond this, the scope of their conclusions, and their arguments for them, are pretty different. They have given reasons for their views at length in various publications, so I hesitate to post such a short summary, but here goes: Dreyfus has been heavily influenced by the existential phenomenologists Heidegger and Merleau-Ponty. This stuff is extremely dense going, but the main idea seems to be a reaction against the Platonic or Cartesian picture of intelligent behavior as being necessarily rational, reasoned, and rule-described. Instead, attention is called to the vast bulk of unreflective, fluent, adaptive coping that constitutes most of human interaction with the world. That the phenomenology of this kind of intelligent behavior shows it to not be produced by reasoning about facts, or applying rules to propositional representations, etc., and that every system designed to produce such behavior by these means has been brittle and not extensible, are reasons to suppose that (1) it's not done that way and (2) it can't be done that way. (These considerations are not intended to apply to systems which are only rule-described at a sufficiently subpersonal level, say at the level of weights of neuronal interconnections. Last I heard, Dreyfus thinks that some flavors of connectionism might be on the right track.) Searle, on the other hand, talks about intentional mental states (states which have semantic content, i.e., which are `about' something), not behavior. His (I guess by now kind of classic) Chinese Room argument is intended to show that no formal structure of states of the sort required to satisfy a computational description of a system will guarantee that any of the system's states are intentional. And if it's not the structure of the states that does the trick, it's probably what the states are instanced in, viz. neurochemistry and neurophysiology, that lends them intentionality. So, for Searle, if you want to build an artificial agent that will not only behave intelligently but also really have beliefs, etc., you will probably have to wire it up out of neurons, not transistors. (Anyway, brains are the only kind of substance that we know of that produce intentional states; Searle regards it as an open empirical question whether it's possible to do it with silicon.) Now you can think that these reasons are more or less awful, but it's just not right to say that these guys have come up with no reasons at all. Paul Kube kube@berkeley.edu ...ucbvax!kube ------------------------------ Date: 14 Jul 86 09:42 PDT From: Newman.pasa@Xerox.COM Subject: Re: common sense Thanks for the reply. Dreyfus' view seems to have changed a bit since I last read anything of his, so I will let that go. However, I suspect that what I am about to say applies to him too. I like your description of Searle's argument. It puts some things in a clearer light than Searle's own stuff. However, I think that my point still stands. Searle's argument seems to assume some "magical" property (I really should be more careful when I use this term; please understand that I mean only that the property is unexplained, and that I find its existence highly unintuitive and unlikely) of biology that allows neurons (governed by the laws of physics, probably entirely deterministic) to produce a phenomena (or epiphenomena if you prefer - intelligence) that is not producible by other deterministic systems. What is this strange feature of neurobiology? What reason do we have to believe that it exists other than the fact that it must exist if the Chineese Room argument is correct? I personally think it much more likely that there is a flaw somewhere in the Chineese Room argument. >>Dave ------------------------------ Date: Mon 14 Jul 86 09:51:27-PDT From: Ken Laws Subject: Searle's Chinese Room There is a lengthy rebuttal to Searle's Chinese Room argument as the cover story in the latest Abacus. Dr. Rappaport claims that human understanding (of Chinese or anything else) is different from machine understanding but that both are implementations of an abstract concept, "Understanding". I find this weak on three counts: 1) Any two related concepts share a central core; defining this as the abstract concept of which each is an implementation is suspect. Try to define "chair" or "game" by intersecting the definitions of class members and you will end up with inconsistent or empty abstractions. 2) Saying that machines are capable of "machine understanding", and hence of "Understanding", takes the heart out of the argument. Anyone would agree that a computer can "understand" Chinese (or arithmetic) in a mechanical sense, but that does not advance us toward agreement on whether computers can be intelligent. The issue now becomes "Can machines be given "human" understanding.?" The question is difficult even to state in this framework. 3) Searle's challege needn't have been ducked in this manner. I believe the resolution of the Chinese Room paradox is that, although Searle does not understand Chinese, Searle plus his hypothetical algorithm for answering Chinese queries would constitute a >>system<< that does understand Chinese. The Room understands, even though neither Searle nor his written instruction set understands. By analogy, I would say that Searle understands English even though his brain circuitry (or homunculus or other wetware) does not. I have not read the literature surrounding Searle's argument, but I do not believe this Abacus article has the final word. -- Ken Laws ------------------------------ End of AIList Digest ******************** From csnet_gateway Wed Jul 16 18:42:33 1986 Date: Wed, 16 Jul 86 18:42:27 edt From: csnet_gateway (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #167 Status: R AIList Digest Wednesday, 16 Jul 1986 Volume 4 : Issue 167 Today's Topics: Seminars - SIDESMAN Silicon Design System (CMU) & Automata Theory, Nuprl Proof Development System (SRI), Conference - AAAI Workshop on Parallel Models, Symbolic Processing & 3rd IEEE Conference on AI Applications ---------------------------------------------------------------------- Date: 9 Jul 1986 1227-EDT From: Laura Forsyth Subject: Seminar - SIDESMAN Silicon Design System (CMU) Wednesday, July 9th, 2:00 p.m. Room 5409 Wean Hall Professor Hilary J. Kahn SIDESMAN A Silicon Design System Which Has Knowledge Based Components Hilary J. Kahn Department of Computer Science University of Manchester Oxford Road Manchester M13 9PL England The SIDESMAN system is a silicon design system which has the following properties: - Facilities to ensure that application processes are technology adaptable - Support for Knowledge Based CAD applications where appropriate - A range of tools to support a general silicon compilation system - Access to a specialist hardware simulation machine This walk will discuss the general structure and motivations behind the SIDESMAN system and will briefly discuss some of the SIDESMAN application processrs. The work detailed is part of a current research project being undertaken by H.J. Kahn and N.P. Filer ------------------------------ Date: Mon 14 Jul 86 11:54:31-PDT From: Richard Waldinger Subject: Seminar - Automata Theory, Nuprl Proof Development System (SRI) Title: Implementing Automata Theory within the Nuprl Proof Development System Speaker: Christoph Kreitz, Dept. of Computer Science, Cornell University Time: Wednesday, 16 July, 4:15pm (Visitors from outside please come to reception desk a little early. Coffee at 3:45 in Waldinger office) Place: EJ228 (New AI Center Conference Room) SRI International, Building E IMPLEMENTING AUTOMATA THEORY with the Nuprl Proof Development System by Christoph Kreitz Department of Computer Science Cornell University Problem solving is a significant part of science and mathematics and is the most intellectually significant part of programming. Nuprl is a computer system which provides assistance with solving a problem. It supports the creation of formulas, proofs and terms in a formal theory of mathematics; with it one can express concepts associated with definitions, theorems, theories, books and libraries. Moreover the formal theory behind it is sensitive to the computational meaning of terms, assertions and proofs, and the computer system is able to carry out the corresponding actions. Thus Nuprl includes computer-aided program development, but in a broader sense it is a system for proving theorems and implementing mathematics. The actual implementation of a mathematical theory, such as the theory of finite automata, with the Nuprl proof development system gives lots of insights into its strengths and weaknesses and shows that it is powerful enough to obtain nontrivial results within reasonable amounts of time. The talk will give a brief overview of Nuprl, its object language and inference rules (Type Theory), and of features of the computer system itself. These features support partial automatization of the problem solving process and extensions of the object language by a Nuprl user. Details of the implementation of automata theory will be shown afterwards. I will describe some of the techniques and extensions to Nuprl which were necessary to formulate and prove theorems from automata theory. In particular, these techniques keep Nuprl proofs small and understandable. I will present a complete Nuprl proof of the pumping lemma and an evaluation of its computational content as performed on a computer. Finally an outline for possible future developments is given. ------------------------------ Date: Mon, 14 Jul 86 16:44:58 edt From: Beth Adelson Subject: Conference - AAAI Workshop on Parallel Models, Symbolic Processing WORKSHOP ON PARALLEL MODELS AND SYMBOLIC PROCESSING Chair: Beth Adelson The purpose of the workshop is to look at current connectionist models in light of traditional AI problems. We will ask how the connectionist and the traditional approaches inform and constrain each other. Several new connectionist approaches to central AI problems will be presented. These new approaches address some issues which have previously been important but difficult in connectionism. SCHEDULE: Drew McDermott Yale University What AI Needs From Connectionism Jerome Feldman University of Rochester Semantic Networks and Neural Nets Geoffrey Hinton Carnegie Mellon University Connectionists Make Better Bayesians: Bayesian Inference In A Connectionist Network David Waltz Thinking Machines Challenges and Directions for Connectionism Organizer: Beth Adelson adelson@yale Before July 26: NSF Washington, DC 20550 (202) 357-9569 After July 26: Tufts University Department of Computer Science Medford, MA 02155 (617) 381-3214 Length: 3 hours: Four 20 minute talks with 10 minutes for questions after each One hour for audience discussion. Date: August 14 Time: 1-4 PM Place: Room 213 in the Law School Attendees: Open to anyone registered at the conference (but audience size is limited to 100) ------------------------------ Date: Fri 11 Jul 86 18:57:46-CDT From: Jim Miller Subject: Conference - 3rd IEEE Conference on AI Applications CALL FOR PAPERS THE THIRD IEEE CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS ORLANDO HYATT REGENCY ORLANDO, FLORIDA FEBRUARY 22-28, 1987 SPONSORED BY THE IEEE COMPUTER SOCIETY This conference is devoted to the application of artificial intelligence techniques to real-world problems. Two kinds of papers are appropriate: - Papers that focus on knowledge-based techniques that can be applied effectively to important problems, and - Papers that focus on particular knowledge-based application programs that solve significant problems. AI techniques include: Application areas include: - Knowledge representation - Science and engineering - Reasoning - Medicine - Knowledge acquisition - Business - Learning - Natural language - Uncertainty - Intelligent interfaces - General tools - Vision - Robotics Only new, significant, and previously unpublished work will be accepted. Two kinds of papers may be submitted: - Full papers: 5000 words maximum, describing significant completed research. - Poster session papers: 1000 words, describing interesting ongoing research. Both categories of papers will be reviewed by the Program Committee. CONFERENCE COMMITTEE General chair: Program committee chairs: Jan Aikins, Aion James Miller and Elaine Rich, MCC Program committee: Jan Aikins, Aion Benjamin Kuipers, University of Texas Byron Davies, Texas Instruments John McDermott, Carnegie-Mellon William Clancey, Stanford University Charles Petrie, MCC Keith Clark, Imperial College John Roach, Virginia Polytechnic Michael Fehling, Teknowledge J. M. Tenenbaum, Schlumberger Mark Fox, Carnegie-Mellon University Harry Tennant, Texas Instruments Bruce Hamill, Johns Hopkins/APL Charles R. Weisbin, Oak Ridge Peter Hart, Syntelligence Michael Williams, Intellicorp Elaine Kant, Schlumberger SUBMISSION INFORMATION - Full length papers: Submit four copies of the paper by September 9, 1986 to the Program Committee chairs, listed below. The first page of the paper should contain the author's (or authors') name, affiliation, and address, a 100 word abstract, and a list of appropriate subject categories, both AI topics and application areas. Conference sessions may be organized around either kind of subject category. Authors are not restricted to only those categories listed above. Accepted papers will be allocated six manuscript pages in the proceedings. - Poster session papers: Submit four copies of a 1000 word abstract by December 1, 1986 to the Program Committee chairs, listed below. Indicate on the front of the paper all appropriate subject categories. Accepted abstracts will be reprinted and distributed at the conference. In addition, authors of accepted poster session papers will be provided with table space at the conference to display examples of their work and to discuss their findings with others. IMPORTANT DATES - Full-length papers must be received by: September 9, 1986 - Authors notifications mailed: October 24, 1986 - Accepted full-length papers returned to IEEE for proceedings: November 15, 1986 - Poster session papers must be received by: December 1, 1986 - Conference: February 22 - 28, 1987, Orlando, Florida FOR FURTHER INFORMATION, CONTACT: Jan Aikins James Miller General Chair Elaine Rich Third IEEE Conference on Program Committee Chairs Artificial Intelligence Third IEEE Conference on Applications Artificial Intelligence Aion Corporation Applications 101 University Avenue MCC Palo Alto, California 94301 9430 Research Blvd. Austin, Texas 78759 ------------------------------ End of AIList Digest ******************** From csnet_gateway Sat Jul 19 06:45:10 1986 Date: Sat, 19 Jul 86 06:45:04 edt From: csnet_gateway (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #168 Status: RO AIList Digest Friday, 18 Jul 1986 Volume 4 : Issue 168 Today's Topics: Queries - PC Expert-System Shell Demos & Garbage Collection Side Effects & Online Almanacs, Policy - Signing with Net Addresses, Literature - LISP Texts & Natural Language, AI Tools - Parallel FCP, Review - July Spang Robinson Report ---------------------------------------------------------------------- Date: 14 Jul 86 06:56 PDT From: A. Winsor Brown, Douglas Aircraft ET&IS Subject: PC Expert-System Shell Demos I am aware of the following low cost or no cost PC expert system shell demo and/or full packages. I am going to use all of them in an internal course on PC based shells/tools, and want each of the students to retain a copy (thus the concern for low priced demonstrators or full systems). Since the course is to address evaluation criteria, actually seeing the tool in use is important. If you know of others would you please let me know, and include a source phone number (and address if the provider was not listed in the 15 June "AI Software for MS-DOS (Long List)"). I will summarize the responses and re-post them here. M.1 with a date of Oct'85 in the "Demonstration Materials" manual; from Teknowledge 415/327-6640. Single disk plus report sent on request; freely copiable for demos. Loading and saving knowledge base disabled in demo; only five knowledge base additions allowed. EXSYS Version 3 from EXSYS, Inc (Albuquerque, NM) 505/836-6676. Copying and distribution encouraged; first copy costs $15. Learning tutorial included with all demo's; full manual in softcopy form in the older 3 diskette version; hard copy form of manual with the newer 2 disk set which also allows saving a 25 rule expert system. Guru initial release (1.00c) from MDBS 317/463-2581. 4 disk set; sent on request (not copy protected but further distribution not proscribed: Copyright protection claimed for diskettes and 50 page "Demonstration Instructions"). On-line help documentation is all that is provided. Definitely need hard disk: 1.2Meg needed just for demo! Can develop small (10 rule) single rule-set expert system with Demo; some other restrictions apply to other parts. 1st Class version 3.0 (3/86) from Programs in Motion 617/653-5093. Demo disk costs $20; re-distribution not currently desired/allowed. Manual not included on diskette; some technical details provided on-line. Personal Consultant version 1.00 from TI 800/527-3500. Available from TI, at no charge; copy protected. 43 page "Demonstration Guide" and 22 page "Technical Report" (on-line help; no documentation per se). Needs full 512K; can run off single floppy; crippled so user cannot save developed system. ESIE version 1.1 from Lightwave Consultants 813/988-5033. Shareware (registration fee is $75). 25 page manual included on diskette. Knowledge Delivery System version of 8/85 from KDS Corporation 312/251-2621. Available from KDS for $25; allowed to be reproduced and distribution verbally proscribed. No manual; not clear about on-line help. Development example limited to 20 cases (examples) from the normal 4096; also has some text size restrictions. Expert System version ??? from PPE 301/977-1489. A public domain tool; available for $20 from PPE too. Manual situation not clear ("program is self documenting" comment from another knowledgeable source). Source code is included! Thank you. --Winsor ------------------------------ Date: Tue, 15 Jul 86 23:46:59 CDT From: David Chase Subject: Query on compilers, optimization, and garbage collection I am looking for references on interactions (good and bad, intended and unintended) between garbage collectors and compilers that (attempt to) do optimizations. For example, if you know of a good optimization that reduces the amount of garbage produced, tell me about it. If you know of an ugly surprise that someone received when they tried to optimize code in a garbage-collected system, tell me about that. I realize that this isn't exactly AI, but I think people reading this list might have some pointers (to other lists, if nothing else). What I already have (no references for ugly surprises): "Optimization of Very High Level Languages-I: Value Transmission and its Corollaries" Schwartz, in Computer Languages, volume 1, pp 161-194 (1975) (copy optimizations, heap->stack allocation conversions) "Experience with the SETL Optimizer" Freudenberger, Schwartz and Sharir, in TOPLAS 5:1 (January 1983) (copy optimizations) "Binding Time Optimization in Programming Languages: Some Thoughts Toward the Design of an Ideal Language" Muchnick and Jones, in POPL 3, 1976 (heap->stack allocation conversions) "Shifting Garbage Collection Overhead to Compile Time" Barth, in CACM 20:7 (July 1977) (reference counting at compile time) "RABBIT: A Compiler for SCHEME" Steele, 1978 (heap->stack allocation conversions for activation records) "Fast Arithmetic in MacLISP" Steele, in 1977 Macsyma Users' Conference (heap->stack allocation conversions for numbers) "An Optimizing Compiler for Lexically Scoped Lisp" Brooks, Gabriel and Steele, in Compiler Construction 1982 (heap->stack allocation conversions for numbers) "A scheme of storage allocation and garbage collection for ALGOL 68" Branquart and Levi, in Algol 68 Implementation (North-Holland, 1971) (compiled marking routines) "Methods of garbage collection for ALGOL 68" Wodon, in Algol 68 Implementation (North-Holland, 1971) (compiled marking routines) David Chase ------------------------------ Date: Wed, 16 Jul 86 16:28 EST From: LEWIS%cs.umass.edu@CSNET-RELAY.ARPA Subject: almanacs and magnitudes I would appreciate any information people could give me on the availability of online almanacs or similar large bodies of broadranging statistical data. Public domain or cheap would be preferable, of course. I also would be interested in hearing about any work that has been done either on AI programs for heuristically estimating the information one finds in almanacs, or on psychological research on human order of magnitude estimates. So far the only place I've seen this subject discussed are the entertaining diatribes on "number numbness" by Douglas Hofstadter in Metamagical Themas, and by Jon Bentley in a recent issue of CACM. Please send replies to me; if there is sufficient interest I will summarize for the digest. Thanks, David D. Lewis Univ. of Massachusetts, Amherst "well, I used to think it was LEWIS@UMASS-CS and lately it's been LEWIS%cs.umass.edu@CSNET-RELAY.ARPA but maybe it's longer now" ------------------------------ Date: Mon, 14 Jul 86 16:21:04 cdt From: Girish Kumthekar Subject: Replying to AIList messages I have been reading messages and find them interesting. However I find that most of the times, the direct address where the reply can be sent is not given. It is typically at the top of the message, and is probably mixed with other details. This forces you to type cntl-z to stop the viewing and come back and note the address at the top. So would you all please give your addresses at the end of messages. (Note that at the top of message, one does'nt know if this message is going to turn out interesting or not ! ). My address is kumthek%lsu@csnet-relay.csnet Thanks in advance Girish Kumthekar (504)-343-5334 ------------------------------ Date: Fri, 11 Jul 86 09:29:42 EDT From: "William J. Rapaport" Subject: LISP texts (followup article) Another good LISP text is the new one by my colleague Stuart C. Shapiro: LISP: An Interactive Approach (Computer Science Press). It is dialect-independent and intended for self-study. We have used it (in both manuscript and published versions) for a number of years at SUNY Buffalo, with great success. ------------------------------ Date: 14 JUL 86 16:34-EST From: PJURKAT%SITVXA.BITNET@WISCVM.ARPA Subject: REFERENCES ON NATURAL LANGUAGE I'm a little slow reading my mail. This is a response to a query in Vol 4 Issue 151 by Gene Guglielmo (sefai@nwc-143b asking for references concerning the representation of natural language on a computer system. Please pass the following on to him: Parisi and Antonucci Essentials of Grammar It presents a represenation of sentences in functional form, that is, predicate(arg1, arg2, ... ) taking into acoount a goodly amount of semantics. I have found it valuable, especially for the analysis of belief systems. Cheers - Peter Jurkat (pjurkat@sitvxa.bitnet) ------------------------------ Date: Fri, 11 Jul 86 09:35:52 -0200 From: Steve Taylor Subject: Parallel FCP We are pleased to announce the availability of a parallel Flat Concurrent Prolog (FCP) [1,2] interpreter for the Intel iPSC Hypercube. The interpreter may be used for initial experiments with parallel logic programming; it includes most of the kernel predicates available in the Logix system. FCP programs may be developed on a uniprocessor under the Logix system, which is announced seperately [3]; this environment operates on the VAX, SUN or Intel 310 systems. Recompilation allows the resulting program to execute on the Intel iPSC hypercube. Simple techniques have been developed to map processes and code to the physical machine [4]. These techniques allow multiple virtual machines to execute concurrently; multiple applications may execute concurrently on a given virtual machine. PLEASE NOTE: The interpreter is an experimental system which has only recently been completed; it is being made available on an informal basis to encourage members of the community to experiment with the language. The handling fee for a non-commercial license to the Parallel FCP Interpreter and the Logix system for the 310 is $250 U.S. To obtain a license form and/or a copy of the Logix user manual write to: Steve Taylor Department of Computer Science The Weizmann Institute of Science Rehovot 76100, Israel To obtain an electronic copy of the license write to: CSnet, Bitnet: steve@wisdom ARPAnet: steve%wisdom.bitnet@wiscvm.arpa Sincerely, Steve Taylor References [1] C. Mierowsky, S. Taylor, E. Shapiro, J. Levy and M. Safra, "The Design and Implementation of Flat Concurrent Prolog", Weizmann Institute Technical Report CS85-09, 1986. [2] A. Houri and E. Shapiro, "A sequential abstract machine for Flat Concurrent Prolog", Weizmann Institute Technical Report CS86-20, 1986. [3] W. Silverman, M. Hirsch, A. Houri, and E. Shapiro, "The Logix system user manual, Version 1.21", Weizmann Institute Technical Report CS86-21. [4] S. Taylor, E. Av-Ron and E. Shapiro, "A Layered Method for Process and Code Mapping", Weizmann Institute Technical Report CS86-17. ------------------------------ Date: WED, 20 apr 86 17:02:23 CDT From: E1AR0002%SMUVM1.BITNET@WISCVM.ARPA Subject: July Spang Robinson Report summary Summary of Spang Robinson Report July 1986, Volume 2, No. 7 (Emphasis on AI and Parallel Procesing) Advanced Decision Systems is using the Butterfly for AI development. They are developing a SCHEME using message passing for the Butterfly. They are developing an expert system to balance work loads and manage faults. The system works well on about 10 nodes but past these points, the system performance does not continue to improve as processors are added. It also takes 20 minutes to reboot the machines. Oak Ridge National Laboratories has been using the NCUBE for machine vision research. NASA is using a FLEX/32 parallel machine to develop an expert system shell and an expert system to predict sun spot activity. CLIPS will run on the FLEX/32 and is an OPS5-like system written in C. In the sun spot sytem, the expert system part of the application will run on the Symbolics with the math part running on the FLEX using parallelism. LUCID is developing an implementation of parallel LISP under subcontract to Stanford. The work is starting on a newly purchased Alliant Computer Systems. Cray Research has some proprietary AI projects in its Applications department. ELXSI is looking for a client who needs AI on mainframe class of machine. It also is looking for a vendor to port AI language to ELXSI. Encore Computers and Masscop has active programs to produce AI languages. The Kemp-Carraway Heart institute is doing image analysis of echo cardiograms using fuzzy logic. It has developed a FLOPS product in which rules can fire in parallel and eliminates the need for "truth maintenance" when rules do not have to be executed sequentially. The system uses fuzzy logic with an OPS-5 syntax. One Forth researcher claims to have designed a 1 million logical inference per second expert system on the Novix NC4000 Forth engine (a $150.00 chip). __________________________________________________________________________ News section Carnegie Group has signed an agreement with Hewlett-Packard to offer its Knowledge Craft expert system shell on the HP 9000 Model 320. Lisp Machines has made 18 changes to their machine to improve reliability. They will have an AVP processor that will be twice the speed of their current processor. They are also working on a LISP chip and on improvement of the development environment for non-LISP machines. Intellicorp has doubled its direct sales force and has established a VAR relationship with AMOCO corporation. TI has sold 1000 Explorer work stations of which 200 are in universities. A key reason for Burroughs recent merger with Sperry is Sperry's AI activity. ------------------------------ End of AIList Digest ******************** From csnet_gateway Sat Jul 19 06:45:23 1986 Date: Sat, 19 Jul 86 06:45:15 edt From: csnet_gateway (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #169 Status: RO AIList Digest Friday, 18 Jul 1986 Volume 4 : Issue 169 Today's Topics: Natural Language - Interactive Architectures, Philosophy - Common Sense & Intelligence Testing & Searle's Chinese Room ---------------------------------------------------------------------- Date: Mon, 14 Jul 86 16:15:01 BST From: ZNAC450 Subject: Interactive Architectures & Common Sense Subject: Re: Architectures for interactive systems? In article <8607032203.AA12866@linc.cis.upenn.edu> brant%linc.cis.upenn.edu@CIS.UPENN.EDU.UUCP writes: >There seems to have been a great deal of work done in >natural language processing, yet so far I am unaware of >any attempt to build a practical yet theoretically well- >founded interactive system or an architecture for one. > >When I use the phrase "practical yet theoretically well- >founded interactive system," I mean a system that a user >can interact with in natural language, that is capable of >some useful subset of intelligent interactive (question- >answering) behaviors, and that is not merely a clever hack. > >Many of the sub-problems have been studied at least once. >Work has been done on various types of necessary response >behavior, such as clarification and misconception correction. >Work has been done on parsing, semantic interpretation, and >text generation, and other problems as well. But has any >work been done on putting all these ideas together in a >"real" system? I would like to try to build such a system but it's not going to be easy and will probably take several years. I'm going to have to build it in small pieces, starting off small and gradually improving the areas that the system can cope with. >I see a lot of research that concludes with >an implementation that solves only the stated problem, and >nothing else. That's because the time taken to construct a sufficiently general system is greater than most people are prepared to put in (measure it in decades),and is so demanding on system resources that with present machines it will run so slowly that the user gets bored waiting for a response (like UN*X :-)). >Presumably, a "real user" will not want to >have to run system A to correct invalid plans, system B to >answer direct questions, system C to handle questions with >misconceptions, and so forth. > No, what we ideally want is a system which can hold a conversation in real time, with user models, an idea of `context', and a great deal of information about the world in general. The last, by the way, is the real stumbling block. Current models of knowledge representation just aren't up to coping with large amounts of information. This is why expert systems, for example, tend to have 3,000 rules or less. It is true that dealing with large amounts of information will become easier as hardware improves and the LIPS (Logical Inferences Per Second) rate increases. However, it won't solve the real problem which is that we just don't know how to organise information in a sufficiently efficient manner at present. >I would be interested to get any references to work on such >integrated systems. If you want to solve the problem of building integrated NLP systems, you are aiming to produce truly intelligent behaviour -- if you accept the definition that AI is about performing tasks by machine which require intelligence in humans. The problems of building integrated NLP systems are the problems of AI, period. I.e.-- Knowledge representation, reasoning by analogy, reasoning by inference, dealing with large search spaces, forming user models etc. I believe that in order to perform these tasks efficiently, we are going to have to look at how people perform these tasks. What I mean by this is that we are going to have to take a long hard look at the way the brain works -- down at the `hardware' level, i.e. neurons. The problem may well be that our approach to AI so far has been too `high-level'. We have attempted to simulate high-level activities of the human brain (reasoning by analogy, symbol perception etc.) by high-level algorithms. These simulations have not been unsuccesssful, but they have not exactly been very efficient either.It is about time we stopped trying to simulate, and performed some real analysis of what the brain does, at the bottom level.If this means constructing computer models of the brain, then so be it. Two books which argue this point of view much better than I can are : Godel, Escher, Bach : An Eternal Golden Braid, by Douglas R. Hofstadter, and Metamagical Themas', also by Douglas R. Hofstadter. >Also, what are people's opinions on this >subject: are practical NLP too hard to build now? No, but they are *very* hard to build. An integrated system would take more resources than anyone is prepared to spend. >Should we >leave the construction of practical systems to private enter- > prise and restrict ourselves to the basic research problems? Not at all. If we can't build something useful at the end of the day then we haven't justified the cost of all this effort. But a lot more basic research has to be done before we can even think about building a practical system. ----francis mcvax!ukc!kcl-cs!fgtbell Subject: Re: common sense References: <8607031718.AA14552@ucbjade.Berkeley.Edu> In article <8607031718.AA14552@ucbjade.Berkeley.Edu> KVQJ@CORNELLA.BITNET.UUCP writes: >My point is this, I think it is intrinically impossible to program >common sense because a computer is not a man. A computer cannot >experience what man can;it can not see or make ubiquitous judgements >that man can. What if you allow a computer to gather data from its environment ? Wouldn't it be possible to make predictive decisions, based on what had happened before ? Isn't this what humans do ? I thought common sense was what allowed one to say what was *likely* to happen, based on one's previous experiences. Is there some reason why computers couldn't do this ? -----francis mcvax!ukc!kcl-cs!fgtbell ------------------------------ Date: Mon, 14 Jul 86 17:02:52 bst From: Gordon Joly Subject: Blade Runner and Intelligence Testing (Vol 4 # 165). The test used in the film is to look for an emotional response to the questions. They are fired off in quick succession, without giving the candidate time to think. He might then get angry... > By the way, the fastest way to identify human > intelligence may be to look for questions that a human will recognize > as nonsense or outside his expected sphere of knowledge ("How long > would you broil a 1-pound docket?" "Is the Des Moines courthouse taller > or shorter than the Wichita city hall?") but that an imitator might try > to bluff through. -- KIL ``Bluff''? What's the payoff? Gordon Joly INET: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk EARN: gcj%UK.AC.QMC.MATHS%UK.AC.QMC.CS@AC.UK UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Tue, 15 Jul 86 11:34:27 bst From: Gordon Joly Subject: Blade Runner and Intelligence Testing (Vol 4 # 165) -- Coda Interesting point about the imitator not being able to discover what is a valid question and what is a piece of nonsense. Reminds me of the theory of automatic integration in computer algebra. The analogy is a bit thin, but basically the algebra system decides first whether or not it has the power (ie there exists an algorithm) before trying to proceed with the integration. If fact, the machine never integrates; it just differentiates in a clever way to get near to the answer. It then alters the result to get the correct answer, and uses the inverse nature of differentiation and integration. I said it was a bit thin; the integrator is working backwards from the answer to find the correct question:-) Gordon Joly INET: gcj%maths.qmc.ac.uk%cs.qmc.ac.uk@cs.ucl.ac.uk EARN: gcj%UK.AC.QMC.MATHS%UK.AC.QMC.CS@AC.UK UUCP: ...!seismo!ukc!qmc-ori!gcj ------------------------------ Date: Mon, 14 Jul 86 21:17:10 est From: Perry Wagle Subject: common sense [this is a response to ucbjade!KVQJ's note on common sense. ] The flaw in Searle's Chinese Room Experiment is that he gets bogged down in considering the demon to be doing the "understanding" rather than the formal rule system itself. And of course it is absurd to claim that the demon is understanding anything -- just as it is absurd to claim that the individual neurons in your brain are understanding anything. Perry Wagle, Indiana University, Bloomington Indiana. ...!ihnp4!inuxc!iuvax!wagle (USENET) wagle@indiana (CSNET) wagle%indiana@csnet-relay (ARPA) ------------------------------ Date: Tue, 15 Jul 86 10:57:50 EDT From: "Col. G. L. Sicherman" Subject: Re: common sense In article <860714-094227-1917@Xerox>, Newman.pasa@XEROX.COM asks: > > However, I think that my point still stands. Searle's argument seems to > assume some "magical" property ... of biology that allows neurons ... > to produce a phenomenon ... that is not producible by other > deterministic systems. > > What is this strange feature of neurobiology? I believe that the mysterious factor is not literally "magic" (in your broad sense), but merely "invisible" to the classical scientific method. A man's brain is very much an _interactive_ system. It interacts con- tinually with all of the world that it can sense. On the other hand, laboratory experiments are designed to be closed systems. They are designed to be controllable; they rely on artificial input, at least in the experimental stage. (When they are used in the field, they may be regarded as intelligent; even a door controlled by an electric eye meets our intuitive criterion for intelligence.) Just what do we demand of "artificial intelligence?" Opening doors for us? Writing music and poems for us? Discoursing on philosophy for us? --Or doing things for _itself,_ and to Hell with humans? I don't think that A.I. people agree about this. ------------------------------ Date: 15 Jul 86 08:16:00 EDT From: "CUGINI, JOHN" Reply-to: "CUGINI, JOHN" Subject: Searle and Understanding This is in response to recent discussion about whether AI systems can/will understand things as humans do. Searle's Chinese room example suggests the extent to which the implementation of a formal system may or may not understand something. Here's another, perhaps simpler, example that's been discussed on the philosophy list. Imagine we are visited by ETS - an extra-terrestial scientist. He knows all the science we do plus a lot more - quarks, quantum mechanics, neurobiology, you-name-it. Being smart, he quickly learns our language and studies our (pitifully primitive) biology, so he knows about how we perceive as well. But, like all of his species, he's totally color-blind. Now, making the common assumption that color-knowledge cannot be conveyed verbally or symbolically, does ETS "understand" the concept of yellow? I think the example shows that there are two related meanings of "understanding". Certainly, in a formal, scientific sense, ETS knows (understands-1) as much about yellow as anyone - all the associated wavelengths, retinal reactions, brain-states, etc. He can use this concept in formal systems, manipulate it, etc. But *something* is missing - ETS doesn't know (understand-2) "what it's like to see yellow", to borrow/bend Nagel's phrase. It's this "what it's like to be a subject experiencing X" that eludes capture (I suppose) by AI systems. And I think the point of the Chinese room example is the same - the system as a whole *does* understand-1 Chinese, but doesn't understand-2 Chinese. To get a bit more poignant, what systems understand-2 pain? Would you really feel as guilty kicking a very sophisticated robot as kicking a cat? I think it's the ambiguity between these senses of understanding that underlies a lot of the debate. They correspond somewhat to Dennett's "program-receptive" and "program-resistant" properties of consciousness. As far as I can see, the lack of understanding-2 in artificial systems poses no particular barrier to their performance. Eg, no doubt we could build a machine which in fact would correctly label colors - but that is not a reason to suppose that it's *conscious* of colors, as we and some animals are. Nonetheless, *even if there are no performance implications*, there is a real something-or-other we have going on inside us that does not go on inside Chinese rooms, robots, etc., and no one knows how even to begin to address the replication of this understanding-2 (if indeed anyone wants to bother). John Cugini ------------------------------ Date: Tue 15 Jul 86 12:31:07-PDT From: Pat Hayes Subject: Re: AIList Digest V4 #166 re: Searle's chinese room There has been by now an ENORMOUS amount of discussion of this argument, far more than it deserves. For a start, check out the BBS treatment surrounding the original paper, with all the commentaries and replies. Searle's position is quite coherent and rational, and ultimately whether or not he is right will have to be decided empirically, I believe. This is not to say that all his arguments are good, but that's a different question. He thinks that whatever it is about the brain ( or perhaps the whole organism ) which gives it the power of intentional thought will be something biological. No mechanical electronic device will therefore really be able to *think about* the world in the way we can. An artificial brain might be able to, it's not a matter of natural vs. artificial, notice: and it's just possible that some other kind of hardware might support intentional thinking, although he believes not; but certainly, it can't be done by a representationalist machine, whose behavior is at best a simulation of thought ( and which, he believes, will never in fact be a successful simulation ). Part of this position is that the behavior of a system is no guide to whether or not it is *really* thinking. If his closest friend died, and an autopsy revealed, to Searles great surprise, that he had been a computational robot all his life, then Searle would say that the man hadn't been aware of anything all along. The 'Turing test' is quite unconvincing to Searle. This intellectual position is quite consistent and impregnable to argument. It turns ultimately on an almost legal point: if a robot behaves 'intelligently', is that enough reason to attribute 'intelligence' to it? ( Substitute your favorite psychological predicate. ) Turing and his successors say yes, Searle says no. I think all we can do is agree to disagree for the time being. When the robots get to be more convincing, let's come back and ask him again ( or send one of them to do it ). Pat Hayes ------------------------------ End of AIList Digest ******************** From csnet_gateway Sun Jul 20 00:45:57 1986 Date: Sun, 20 Jul 86 00:45:52 edt From: csnet_gateway (LAWS@SRI-STRIPE.ARPA) To: ailist@sri-stripe.arpa Subject: AIList Digest V4 #170 Status: RO AIList Digest Saturday, 19 Jul 1986 Volume 4 : Issue 170 Today's Topics: Philosophy - Creativity and Analogy & Life and Intelligence & Gibson's Theory of Perception & Representationalist perception, Humor - Circular Reasoning as a Tool ---------------------------------------------------------------------- Date: Tue, 15 Jul 86 09:31 EST From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA Subject: Creativity and Analogy I believe that Jay Weber and I mostly agree on the relation between an abstraction and an analogy as well as the relation between the respective spaces of abstractions and analogies (linguistic "slipperiness" notwithstanding). What I disagreed with is the notion of some absolute abstraction hierarchy implicit in Jay's comments: > ... Each analogy corresponds to a node in an abstraction hierarchy which > relates all of the sub-categories, SO THE SPACE OF ANALOGIES MAPS ONTO THE > SPACE OF ABSTRACTIONS,..... The distinction between an absolute abstraction hierarchy and multiple abstraction lattices (the term I used in an earlier communication) is central to the discussion of creativity, that is if you accept that creativity is the art of making INTERESTING analogies (or abstractions). Implicit in this definition is a choice between candidate analogies--a choice not available in an abstraction hierarchy. In all fairness, Jay never states explicitly that the world can only be represented by a single abstraction hierarchy. > Proper scientists (by definition) do not construct theories about things > that cannot be empirically examined, e.g. using structure mapping functions > to model the communal descriptive definition of the English word > "creativity". Scientists pick testable domains such as problem solving > where you can test predictions of a particular theory with respect to > correct problem solving. I am surprised by Jay's definition of "proper scientists". As to modeling the communal descriptive definition of "creativity", how else could one begin to emulate this elusive property? I am surprised at his choice of a model problem for "proper scientists"--something as general as problem solving. If problem solving by induction or by analogy are proper domains, why isn't problem solving by "creativity" acceptable? The fact that the word means slightly different things to different people does not justify its exclusion from the class of "proper domains". It is fairly obvious that we have similar perceptions about what the word "creativity" means--how else could we be having this discussion? > In the past, scientists have left debate over > such concepts as "truth" and "beauty" to philosophers, and I think we > should do the same with "creativity" and "intelligence". Who are the "we" in this sentence? If "we" refers to the AIList, doesn't that include philosophers interested in AI? > In Cognitive Science, researchers have too often exaggerated the impact > of their work through the careless and unscientific use of such terms. What is the lesson to be learnt here? Do not use words like "creativity" that sound pompous? If I want to develop a program that has this interesting property I will need to give this property a name. What would be more natural than "creativity"? ------------------------------ Date: Wed, 16 Jul 86 21:54:42 PDT From: larry@Jpl-VLSI.ARPA Subject: Definitions of Life, Intelligence, and Creativity Yes, even defining "intelligence" and "creativity" is very difficult, much less studying their referents scientifically. But I think it's possible. General systems theory helps, despite some extravagances and errors its followers have committed. (Stavros McKrakis pointed out a paper to me by Berliner that discusses some of the worst.) It resolves the difference between reductionism and mysticism in a useful way, by raising the status of information to a physical metric as important as space, time, charge, etc. GST focuses on the fact that when parts are bound together, interaction effects bring into existence characteristics which none of the parts possess. Science is organized around this, with physics concentrating on atomic and subatomic domains, chemistry concentrating on molecular interactions, and so on. The universe is divided up into layers of virtual machines, and for the same reason we do it in computer science: intellectual parsimony. The biologist, for instance, doesn't have to know whether the hydrogen atoms in a sample of water have one, two, or three neutrons. Water functions much the same regardless. (There ARE fascinating and subtle differences some researchers are investigating.) Definition (and investigation) of intelligence and creativity are bound up with another "impossible to define" word: life. "Life" is a label I give to systems which maintain their existence in hostile environments by continuously remaking themselves. Over a period of time (sometimes quoted as seven years for humans), each organism exchanges all of its individual atoms with the environment. Yet it still "lives" and "has the same identity" because its pattern is (essentially) the same. Obviously each organism must somehow "know" the pattern it must maintain and the safe limits for change before corrective action is taken. Biologists have concluded that genes (and gene-like adjuncts outside them) don't contain enough information. Studies point to the conclusion that some of this information is stored in the universe itself, in the form of natural laws for instance. Additionally the organism must be able to sense itself, compare itself with the desired pattern, and take action to correct for deviations. In some cases it acts on its environment (pushing away a danger, for instance); in others it acts on itself (say, standing tall and bristling to frighten attackers). "Intelligence" I would define in very general terms: storing information that describes an organism's external and internal universe, comparing and other- wise processing information in the service of its survival and health, and controlling its action. (Obviously, this definition could be formalised and made more precise, but it will do as a first cut.) It may be protested that these terms are too general, that too many things would thus be classified as alive and/or intelligent. I would say that it's more important to subclassify intelligence and study the interactions and limits of different kinds of intelligence, to study the physical bases of intelligence. I see nothing wrong with saying that a computer program of the Game of Life is really alive (in a very restricted and limited sense which can be couched in formal terms) or that a virus has (very limited, specific kinds) of intelligence. I see it as useful parsimony that intelligence is defined as a multi-dimensional continuum with protozoa near one end, humans in the middle on many continua, and who knows what at the upper end(s). "Creativity" is a particular kind of intelligence. It can be recognized by its products: ideas, actions, or objects that did not exist before. This is not an absolute criteria; it's not all that rare for even those we recognize as geniuses to create the same idea independently (or as much as humans can be who are working in the same field). There are middle and low grades of creativity as well: the same "Chicken Kiev" jokes conceived by hundreds of people on the same day, for instance. Obviously, these new things don't appear from nowhere. There are conservation laws in thought as well as in physics (though very different ones). These novelties are made up of percepts/concepts already in memory, selected and bound to create a system with emergent properties that convince us (or don't) that we've come across something original. (I've gone into the dynamics of creativity in a previous message and won't repeat myself.) Larry @ jpl-vlsi ------------------------------ Date: 15 Jul 1986 11:06 EDT From: ihnp4!mtuxo!hfavr@ucbvax.berkeley.edu Subject: Gibson's theory of perception I have not read Kelley's book, but as a psychologist I am familiar with Gibson's "environmental" (or "ecological") theory of perception. In the standard contemporary conceptualization of perception, from which Gibson dissented, the input to the perceptual process is thought to be the sensory impression; for example, in visual perception, the pattern of retinal stimulation. According to the standard theory, the task of the perceptual system is to derive, from that pattern, a representation whose features are analogous to those features of the environment which originally caused the retinal pattern. If the perceptual system is thought of as physically limited to the eye and the brain, the standard view is close to being a logical necessity. It is from this conceptualization that Gibson dissented. In Gibson's view, the perceptual system is not limited to the confines of the organism, but extends into the environment. In the course of its evolution, the organism has assimilated physical mechanisms present in its natural environment to function as integral parts of its perceptual system. Thus, the perceptual processes implemented in the eye and the brain have evolved to function as the back-end of an integral process of perception that begins at the perceived object. In this view, the natural light sources present in the environment, the reflective properties of the surfaces of objects, and the optical characteristics of the atmosphere are as much a part of the human perceptual system as the eyes and the brain. Thus, the retinal stimulation pattern is not the input to perception, but rather an internal stage in the process. The input to the perceptual process is the object itself; the output is the organism's awareness of the object. The information contained in this awareness is the original, and not a re- (or transformed), presentation of the object to consciousness. According to Gibson, the experimental psychologist's laboratory use of two-dimensional representations, tachistoscopic stimuli, illusions, and other materials that were not part of the ecological environment in which the human perceptual system evolved, amounts to studying the human perceptual system with some of its key parts removed. This is rather like trying to find out how a computer works after pulling out some of its chips, or deducing normal physiology from the results of the surgical removal of organs. To yield valid information, the results of such experiments must be interpreted with special attention to the fact that one is not studying an intact or properly functioning system. Adam Reed (ihnp4!npois!adam) ------------------------------ Date: Wed 16 Jul 86 16:56:49-PDT From: John Myers Subject: Re: AIList Digest V4 #166 I do not believe a concept of self is required for perception of objects. Concepts needed for the perception of objects include temporal consistency, directional location, and differentiation; semantic labeling (i.e., "meaning" or "naming") is also useful. None of these require the concept of a self who is doing the perceiving. The robots I work with have no concept of self, and yet they are quite successful at perceiving objects in the world, constructing an internal world model of the objects, and manipulating these objects using the model. (Note that a "world model" consists of objects' locations and names--temporal consistency is assumed, and differentiation is implicit. Superior world models include spatial extent and perceptual features.) I would argue that they are moving by "reflex"--without true understanding of the "meaning" of their motions--but they certainly are able to truly perceive the world around them. I believe lower-level life-forms (such as amoebas, perhaps ants) work in the same manner. When such-and-such happens in the world, run program FOO which makes certain motions with the effectors, which (happens to) result in "useful things" getting accomplished. I think this describes what most of consciousness is: (1) being able to perceive things in the environment, (2) knowing the meaning of these things, and (3) being able to respond in an appropriate manner. Notice that all of these concepts are vague; different degrees of 1,2,3 represent different degrees of consciousness. Self-consciousness is more than consciousness. The concept of self is not required for conscious beings, and it certainly is not required for perception. John Myers~~ ------------------------------ Date: Thu, 17 Jul 86 18:10:29 -0200 From: Eyal mozes Subject: Re: Representationalist perception David Sher writes: >I may be confused by this argument but as far as visual perception is >concerned we are certainly not aware of the firing rates of our individual >neurons. We are not even aware of the true wavelengths of the light that >hits our eyes. We have special algorithms built into our visual hardware >that implements an algorithm that decides based on global phenomena the >color of the light in the room and automatically adjusts the colors of >percieved objects to compensate (this is called color constancy). However >this mechanism can be fooled. Given that we don't directly percieve >the lightwaves hitting our eyes how can we be directly percieving objects >in the world? That's exactly the point. We DON'T perceive lightwaves, images or neuron firing-rates; we directly perceive external objects. The light waves, our eyes, and the neural mechanisms (which are MECHANISMS, not algorithms) are not the objects of our perception; they are the MEANS by which we perceive objects. This will seem implausible only if you accept the diaphanous model of awareness. Stephen Barnard writes: >Consider what happens when we look at a realistic >painting. We can, at one level, see it as a painting, or we can see >it as a scene with no objective existence whatsoever. How could this >perception possibly be interpreted as anything but an internal >representation? Sorry, I can't follow your argument. Of course, a realistic painting is a representation; but it is not an INTERNAL representation. Gibson's books do contain long discussions of paintings; but he specifically distinguishes between looking at a painting (in which case you are perceiving a representation of the object) and directly perceiving the object itself. >Gibson emphasized the richness of the visual stimulus, >arguing that much more information was available from it than was >generally realized. But to go from this observation to the conclusion >that the stimulus is in all cases sufficient for perception is clearly >not justified. Gibson did not deny that there are SOME cases (for example, many situations created in laboratories) in which the stimulus is impoverished. His point was that these cases are the exception, rather than the rule. Even if we agree that in those exceptional cases there is some inference from background knowledge, this doesn't justify concluding that in the normal cases, where the stimuli do uniquely specify the external object, inference also goes on. Since I can't possibly do justice to these issues in a short electronic message, let me repeat my recommendation of Kelley's book. It discusses all these issues in detail, and presents them very clearly. I'm sure it will be of great value even to those who'll end up disagreeing with its conclusions. Eyal Mozes BITNET: eyal@wisdom CSNET and ARPA: eyal%wisdom.bitnet@wiscvm.ARPA UUCP: ..!ucbvax!eyal%wisdom.bitnet ------------------------------ Date: Fri 11 Jul 86 10:42:05-CDT From: David Throop Subject: Circular Reasoning as a Tool CIRCULAR-REASONER: A Knowledge-Representation Tool for Couches The classic question "How long will it take my brother-in-law and his friend Larry to get the couch from the living room, around a tight corner and into the guest bedroom?" has inspired several advances in AI knowledge representation. The spatial and temporal aspects of the problem have proved particularly difficult. Early work in logic representations was able to show that (Couch X) could be unified with (Furniture X) and push the intractable aspects back a level of abstraction. Rule based systems were able to diagnose Larry's wrenched back after the first attempt, and show that if anybody ever solved the intractable spatial problems, they should leave the answer in the knowledge base. Frame based systems showed that intractable problems could be pushed back a further level through inheritance. Causal reasoning systems can reason about all of the possible behaviors of the couch as it undergoes the process of being shoved around the corner, and move the temporal and spatial questions back into a meta-knowledge-base. I propose to generalize these methods for pushing back hard problems. In particular the program CIRCULAR-REASONER represents these four knowledge representation systems as a linked list. This linked list can be NCONCed to itself so that each level, another representation is just around the corner. Spatial and temporal aspects can be handled by routines that access this list recursively, so that hard problems can be sent away and never come back. David Throop ------------------------------ End of AIList Digest ********************