From in%@vtcs1 Thu Mar 5 17:21:12 1987 Date: Thu, 5 Mar 87 17:21:04 est From: vtcs1::in% To: vpi-ailist@vtcs1.cs.vt.edu Subject: Status: RO Received: from relay.cs.net by vtcs1.cs.vt.edu; Wed, 4 Mar 87 19:31 EST Received: from relay.cs.net by RELAY.CS.NET id ai20710; 4 Mar 87 2:26 EST Received: from sri-stripe.arpa by RELAY.CS.NET id aa24816; 4 Mar 87 2:24 EST Date: Tue 3 Mar 1987 22:57-PST From: AIList Moderator Kenneth Laws Reply-to: AIList@sri-stripe.arpa US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V5 #63 To: AIList@sri-stripe.arpa AIList Digest Wednesday, 4 Mar 1987 Volume 5 : Issue 63 Today's Topics: Administrivia - Moderating Best Lispm/WorkStation Discussion & Timing of the INtelliGenT Discussion, Expert systems - Definition ---------------------------------------------------------------------- Date: Tue, 3 Mar 87 09:29:45 PST From: TAYLOR%PLU@ames-io.ARPA Subject: Moderating Best Lispm/WorkStation(again) I am posting this again(?) because I am not sure it was successful the first time (it came back undelivered). It has been suggested that I moderate, summarize and the post summary of this discussion, instead of dumping it on Ken Laws (AIList). I agree. Therefore, please e-mail all responses, questions, flames, etc. to me. Thanks - Will Will Taylor - Sterling Software, MS 244-17, NASA-Ames Research Center, Moffett Field, CA 94035 arpanet: taylor@ames-pluto.ARPA usenet: ..!ames!plu.decnet!taylor phone : (415)694-6525 [It wasn't my suggestion, but sounds good to me. Thanks. -- KIL] ------------------------------ Date: 3 Mar 87 14:56:47 GMT From: allegra!ether@ucbvax.Berkeley.EDU (David Etherington) Subject: Re: What is this "INtelliGenT"? Please, can we skip recycling the discussion of what AI *is*? If people really must post on the subject, perhaps they could read the last few months' postings first. Deja vu! ------------------------------ Date: 2 Mar 1987 1415-EST From: Bruce Krulwich Subject: Expert systems There seems to be a trend nowadays to use the phrase "expert systems" to mean rule-based systems, not to mean any systems that mimick expert behavior. While I'm not sure I like the terminology, I think that it's beneficial to have a seperate catagory for rule-based-systems work, since that's often very different from other A.I. work (especially in describing research work) This opinion may, however, be biased by my opinions of current work in AI and expert systems. What do others think?? Bruce Krulwich If you're right 95% of the time, why worry about the other 3% ?? arpa: krulwich@c.cs.cmu.edu bitnet: krulwich@c.cs.cmu.edu Any former B-CC'ers out there?? uucp: ... !seismo!krulwich@c.cs.cmu.edu ------------------------------ Date: 2 Mar 87 03:06:55 GMT From: rpics!yerazuws@seismo.css.gov (Crah) Subject: Re: dear abby.... In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes: > > Dear Abby. My friends are shunning me because i think that to call > a program an "expert system" it must be able to explain its decisions. > "The system must be able to show its line of reasoning", I cry. They > say "Forget it, Roy... an expert system need only make decisions that > equal human experts. An explanation facility is optional". Who's > right? While you're developing an expert system, you have to know not just that it inferred something incorrectly, but WHY it inferred it incorrectly. Looking through 4,000 rules trying to find the one with a typo is no fun, no fun at all. Secondly, once you and your expert have convinced yourself that the system is right, you must now convince your first set of users that the system is right, too. These users may not be as expert as *your* expert, but they have some knowledge of the subject. Perhaps a few of them are even more expert than your expert in some narrow subfield. It behooves you to gain acceptance and knowledge from this group, and if they perceive that the expert system is a "black box", they will have no encouragement to assist in the final tweaking and debugging. To be useful, your system must not only be correct. It must be accepted and used! Personal experience- People, including the expert whose knowledge has been captured, don't like (maybe don't trust?) a black-box expert system, if they can't ask it why it gave the answer it did. -Bill Yerazunis "...these guys had "Thugs 'R' Us" stencilled all over them" ------------------------------ Date: 2 Mar 87 15:58:29 GMT From: cbatt!osu-eddie!tanner@ucbvax.Berkeley.EDU (Mike Tanner) Subject: Re: dear abby.... Leaving aside the utility of explanations in developing a system and in convincing users it is behaving properly there is this: Experts are capable of explaining their reasoning, justifying conclusions, etc. Hypothesis: they are able to do this partly because of the way their knowledge is organized and used in problem-solving. Therefore, if your expert system is incapable of explaining itself you probably haven't got the knowledge organization and problem solving strategy right. (Granted, it's only a hypothesis. It seems right to me. I'm in the process of working on a PhD dissertation on how knowledge organization and problem-solving strategy can help produce good explanations. Doesn't exactly support the hypothesis, but it should clarify it a bit.) This assumes you're interested in how knowledge-based problem-solving works. If all you want is an expert system, ie, a system which gets right answers, then you're back to utility arguments for explanation. (Though, I don't think you'll be successful at getting good performance without this understanding.) -- mike ARPA: tanner@ohio-state.arpa UUCP: ...cbosgd!osu-eddie!tanner ------------------------------ Date: 2 Mar 87 15:36:17 GMT From: ulysses!sfmag!sfsup!saal@ucbvax.Berkeley.EDU Subject: Re: dear abby.... In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes: > >Dear Abby. My friends are shunning me because i think that to call >a program an "expert system" it must be able to explain its decisions. >"The system must be able to show its line of reasoning", I cry. They >say "Forget it, Roy... an expert system need only make decisions that >equal human experts. An explanation facility is optional". Who's >right? >Signed, >Un*justifiably* Compromised >Roy Masrani, Alberta Research Council It all depends. During development it is absolutely necessary for the system to give its reasoning, if only as a useful debugging tool. (Is the system using the correct logic to get to the decision.) Once it is "in production" (the field) it may not be as important tot give an explanation every time. This is particularly the case when the expert system is used to help do some of the more mundane tasks on a very frequent basis. There are 2 reasons for this. (1) the user may be able to agree intuitively after deriving the answer - the machine has just helped speed the process. OR (2) If a production ES has been converted to a compiled language, the code to express the rationale may be removed to speed up run time. Sam Saal ------------------------------ Date: 2 Mar 87 20:24:38 GMT From: tektronix!sequent!mntgfx!franka@ucbvax.Berkeley.EDU (Frank A. Adrian) Subject: Re: dear abby.... In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes: >"expert system" ... must be able to explain its decisions. VS. >... expert system need only make decisions that equal human experts. > An explanation facility is optional". Well, given the level of explaination most human experts give (e.g., "Well, I did it this way because it felt right," or "Gosh, I don't know, it seemed like a good idea at the time."), I tend to agree with number two. In fact, has anyone done an expert system which automatically spits out one of the above phrases (or any number of similar phrases) as an "explaination"? Could bring the damn things closer to Turing capability as percieved by the user... "What the hell are YOU asking for," might get the proper amount of arrogance I've seen in most experts (:-). Frank Adrian Mentor Graphics, Inc. ------------------------------ Date: 2 Mar 87 20:37:59 GMT From: ihnp4!alberta!calgary!arcsun!rob@ucbvax.Berkeley.EDU (Rob Aitken) Subject: Re: dear abby.... In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes: > > Dear Abby. My friends are shunning me because i think that to call > a program an "expert system" it must be able to explain its decisions. > "The system must be able to show its line of reasoning", I cry. They > say "Forget it, Roy... an expert system need only make decisions that > equal human experts. An explanation facility is optional". Who's > right? > > Signed, > > Un*justifiably* Compromised > Dear Mr. Compromised: You should ask yourself whether you want a complete, intelligible explanation facility, or just the basics (i.e. "The answer is X because Rule Y says so"). If it is the latter, your friends are wrong and you should tell them so. If the former, your friends are probably programmers and lazy ones at that. You should find new friends. Abby. > Roy Masrani, Alberta Research Council > Roy Masrani, Alberta Research Council P.S. You don't need to specifically include a .signature ------------------------------ Date: Tue, 3 Mar 87 13:29:38 EST From: Bruce Nevin Subject: RE: dear Abby We humans do not usually backtrack over a line of reasoning that led to a conclusion. Instead, we reconstruct what such a line of reasoning might plausibly be. It's called rationalization. How wonderful it is to be rational beings, for we can make plausible whatever conclusions we cherish. --Ben Franklin (paraphrase from memory) As the ordinary usage of the term suggests, rationalization can and often does lead us astray, but that is a critique of the quality of the particular line of reasoning that an individual might reconstruct to rationalize or `make rational' a given conclusion. We reach conclusions by means that are not guaranteed. We need valid rationalization to check them out. Pearce made the point that mathematical reasoning is a tidy pyramidal structure erected after the fact, and that it is better both for presentation and for pedagogy to show the path actually followed, even though it appears less elegant. Few have done this. Does this mean Pearce would advocate expert systems explaining by retracing? I think not, because he explicitly recognized the importance of intuitive hunches in mathematical and logical work. The proof is merely to validate conclusions reached by a less respectable path--to rationalize them. Since our expert systems cannot emulate hunches, a useful approach is to check out conclusions human users have a hunch about. Can they validly be rationalized? Isn't this in fact the use to which many users prefer to put expert systems like Palladian's financial consultant? What is an expert? Some say: an expert is someone who knows a great deal about his subject. I prefer: an expert is someone who knows some of the worst mistakes that can be made in his subject, and how to avoid them. --Werner Heisenberg Bruce Nevin bn@cch.bbn.com (This is my own personal communication, and in no way expresses or implies anything about the opinions of my employer, its clients, etc.) ------------------------------ Date: 3 Mar 87 17:54:03 GMT From: trwrb!aero!coffee@ucbvax.Berkeley.EDU (Peter C. Coffee) Subject: Re: dear abby.... In article <3269@osu-eddie.UUCP> tanner@osu-eddie.UUCP (Mike Tanner) writes: >If all you want is an expert system, ie, a system which gets >right answers, then you're back to utility arguments for explanation. I agree with everything else Mike said about this issue, but it seems to me that the label "expert system" _should_ mean something _more_ than "a system that gets right answers." We've had useful programs, implicitly applying "expert" knowledge, for a long time: the new label should reflect new capabilities. Hayes-Roth et alia, in _Building_Expert_Systems_, say the following: "...[E]xpert systems differ from the broad class of AI tasks in several respects...they employ self-knowledge to reason about their own inference processes and provide explanations or justifications for conclusions reached." This is one of the milestone texts in the field, and definitions are useful things: it seems to me that disputes over whether explanation is "needed" before you can call it an expert system are missing the point. We _have_ what seems to me to be a mainstream definition for the term; if we want to talk about a system that _doesn't_ do explanation, can't we just call it a computer program (or a parser, or a pattern recognizer, or whatever) instead of trying to stretch the popular label to fit it? Constructively, I hope, Peter C. ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Thu Mar 5 18:02:12 1987 Date: Thu, 5 Mar 87 18:02:03 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #64 Status: R AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 64 Today's Topics: Seminars - A Stochastic Genetic Search Method (CMU) & Hypothesis Formation (Rutgers) & Creative Analogies in Scientific Progress (UPenn) & On Visual Formalisms (CMU), Conference - Workshop on Coupling Symbolic and Numeric Computing & AAAI Workshop on Planning for Autonomous Mobile Robots & Computing and Society in Seattle, Preceding AAAI & HICSS-21 Call For Papers ---------------------------------------------------------------------- Date: Sun 1 Mar 87 17:49:12-EST From: Dave Ackley Subject: Seminar - A Stochastic Genetic Search Method (CMU) David H. Ackley Carnegie Mellon Computer Science doctoral dissertation defense Tuesday, February 24, 1987 at 1pm Wean Hall 5409 "Stochastic iterated genetic hillclimbing" Abstract In the "black box function optimization" problem, a search strategy is required to find an extremal point of a function without knowing the structure of the function or the range of possible function values. Solving such problems efficiently requires two abilities. On the one hand, a strategy must be capable of "learning while searching": It must gather global information about the space and concentrate the search in the most promising regions. On the other hand, a strategy must be capable of "sustained exploration": If a search of the most promising region does not uncover a satisfactory point, the strategy must redirect its efforts into other regions of the space. This dissertation describes a connectionist learning machine that produces a search strategy called "stochastic iterated genetic hillclimbing" (SIGH). Viewed over a short period of time, SIGH displays a coarse-to-fine searching strategy, like simulated annealing and genetic algorithms. However, in SIGH the convergence process is reversible. The connectionist implementation makes it possible to "diverge" the search after it has converged, and to recover coarse-grained information about the space that was suppressed during convergence. The successful optimization of a complex function by SIGH usually involves a series of such converge/diverge cycles. SIGH can be viewed as a generalization of a genetic algorithm and a stochastic hillclimbing algorithm, in which genetic search discovers starting points for subsequent hillclimbing, and hillclimbing biases the population for subsequent genetic search. Several search strategies---including SIGH, hillclimbers, genetic algorithms, and simulated annealing---are tested on a set of illustrative functions and on a series of graph partitioning problems. SIGH is competitive with genetic algorithms and simulated annealing in most cases, and markedly superior in a function where the uphill directions usually lead \away/ from the global maximum. In that case, SIGH's ability to pass information from one coarse-to-fine search to the next is crucial. Combinations of genetic and hillclimbing techniques can offer dramatic performance improvements over either technique alone. ------------------------------ Date: Mon, 2 Mar 87 13:04 EST From: FAWCETT@RED.RUTGERS.EDU Subject: Seminar - Hypothesis Formation (Rutgers) On Thursday, March 19th at 10:30 AM, Prof. Lindley Darden from the University of Maryland will speak on her work on hypothesis formation. The room will be announced shortly. An abstract and a summary of her interests follow. "Hypothesis Formation Using Part-Whole Interrelations" Lindley Darden This paper discusses an implementation, called SUTTON, of strategies for rediscovering the chromosome theory of heredity. Walter Sutton formulated the theory in the early 20th century, by postulating interrelations between the fields of cytology and genetics. Knowledge from these fields during that period is represented in a frame-based system, and rules for using knowledge from one field to guide hypothesis formation in the other are implemented in LISP. In particular, the discovery that the gene is part of the chromosome is simulated, and general rules for part-whole reasoning are investigated, including rules for inheritance and propagation of causal relations in part-whole hierarchies. Keywords: Hypothesis formation, scientific discovery, learning, identity relation, part-whole relation, causality. Lindley Darden is an Associate Professor in the Departments of Philosophy and History and a member of the graduate faculty in the Committee on the History and Philosophy of Science at the University of Maryland, College Park. She is currently serving in the second year of a half-time research appointment in the University of Maryland Institute for Advanced Computer Studies. This work was done in collaboration with Roy Rada of the National Library of Medicine. Her research interests include reasoning in scientific discovery (including analogical reasoning and formation of abstract theory types) and knowledge representation techniques for biological knowledge. Her address is Department of Philosophy, University of Maryland, College Park, Maryland 20742 and darden@mimsy.umd.edu. (In addition, Prof. Darden gave an invited talk at last summer's AAAI entitled "Viewing History of Science as Compiled Hindsight".) ------------------------------ Date: Tue, 3 Mar 87 19:11 EST From: Tim Finin Subject: Seminar - Creative Analogies in Scientific Progress (UPenn) SPECIAL JOINT COLLOQUIUM Computer Science, Psychology and Physics University of Pennsylvania THE ROLE OF CREATIVE ANALOGIES IN SCIENTIFIC PROGRESS: COMPUTER MODELING Professor Douglas R. Hofstadter, University of Michigan 2:30 p.m. Wednesday, March 4, 1987 Tea served at 2:00 in the Faculty Lounge (2E17) David Rittenhouse Lab - Auditorium A1 The Copycat project is a computer model of analogical thought processes, particularly ones in which a creative or daring leap is made of the sort that when done in science often postulates new theoretical constructs or objects (genes, particles, etc.). Examples of such analogies in science will be presented and the copycat model will be discussed. ------------------------------ Date: 3 Mar 87 10:23:53 EST From: Theona.Stefanis@g.cs.cmu.edu Subject: Seminar - On Visual Formalisms (CMU) PS SEMINAR MONDAY, 9 March WeH 5409 3:30 On Visual Formalisms David Harel Weizmann Inst., Rehovot, Israel (At CMU for the year) A general mathematical object of diagrammatic nature, the higraph, is presented. Higraphs borrow and extend ideas from Venn-diagrams, graphs and hypergraphs. They constitute a visual formalism for describing various kinds of complex entities, particularly those that involve many sets of objects having intricate structural (i.e., set-theoretic) interrelationships as well as additional relations af dynamic, causal or other nature. Higraphs appear to have many applications, as well as a rich theory that awaits further research. We shall exhibit a number of applications in database theory (entity-relationship diagrams), artificial intelligence (semantic and associative nets) and concurrent reactive systems (statecharts). Statecharts constitute a natural extension of conventional state-transition diagrams in ways that make them appropriate for describing large real-world systems, and they will be described in the talk in some detail. __________________________________________ ------------------------------ Date: 4 Mar 87 02:29:21 GMT From: ssc-vax!bcsaic!tedk@BEAVER.CS.WASHINGTON.EDU (Ted Kitzmiller) Subject: Conference - Workshop on Coupling Symbolic and Numeric Computing Due to electronic mail system problems and other manifestations of Murphy's law, the deadline for paper submittals to the workshop on coupling symbolic and numeric computing (see AAAI magazine Winter issue) has been extended until late March. If you had previously sent me an electronic mail message about the workshop and have not received a response, please resend your message. It appears that in many instances in which I responded to queries about the workshop via the network, the responses were not successfully delivered. Unfortunately, in these instances no evidence of a problem was indicated. Please contact me at the e-mail address, telephone, or mail address below (if you have not done so within the last week) if you are interested. Please include both your phone number and US mail address along with an explicit e-mail incantation to your site. Ted Kitzmiller Boeing Advanced Technology Center US Mail: MS 7L-64 / PO Box 24346 / Seattle / Washington / 98124-0346 Parcel Post: MS 7L-64 / 2760 160th Avenue SE / Bellevue / Washington / 98008 Phone: (206) 865-3227 E-mail: tedk@boeing.com ------------------------------ Date: Thu, 26-FEB-1987 15:45 EST From: MILLER%VTCS1.BITNET@wiscvm.wisc.edu Subject: Conference - AAAI Workshop on PLANNING FOR AUTONOMOUS MOBILE ROBOTS Call for Participation and abstracts: Workshop on PLANNING FOR AUTONOMOUS MOBILE ROBOTS July 16, 1987, The University of Washington, Seattle, WA Sponsored by AAAI _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Most mobile robot projects have concentrated on robots with specific missions (e.g., complete errands one and two, follow this road for three miles). Yet a truly autonomous robot would have its mission described at a much higher level. Its programming would have to derive specific tasks to be accomplished based on unpredictable (and perhaps not even previously classifiable) conditions in its environment. This opens new issues for the type of planning system necessary to guiding autonomous robots. The purpose of this workshop would be to discuss the planning and knowledge requirements of an autonomous exploratory robot such as a Mars Rover. How would such a robot decide on a course? What kind of risk assessment is necessary before deciding to make a dangerous observation? What types of knowledge are necessary for recognizing something as being interesting, or dangerous? What role will physical knowledge play in safe navigation? Is either incremental or opportunistic planning necessary for dealing with a dynamic world? What kind of demands would the planning system place on the sensory system? Among the topics of interest are: *Spatial Representation *Map Building *Planning Under Uncertainty *Risk Analysis *Planning in Dynamic Domains *Physical Reasoning *Spatial and Temporal Reasoning *Sensor Coordination *Experience-Based Planning *Route Planning Those interested in participating in the workshop should submit a short abstract (no more than two pages) of your work you would wish to present. Mail two copies of your abstract (hard copy only) before April 15, 1987, to either of the workshop organizers. Invitations for workshop participation will be sent out by May 15, 1987. David Miller David Atkinson 562 McBryde Mail Stop 510-202 Department of Computer Science Jet Propulsion Laboratory Virginia Tech Cal Tech Blacksburg, VA 24061 4800 Oak Grove Drive Pasadena, CA, 91109 (703) 961-5605 (818) 577-6603 miller%vtcs1@bitnet-relay.arpa atkinson@usc-ecl.arpa ------------------------------ Date: Tue, 03 Mar 87 08:59:31 PST From: jon@june.cs.washington.edu (Jon Jacky) Subject: Conference - Computing and Society in Seattle, Preceding AAAI (This was sent around in early December - due date 4/1 now approaching) Call for Papers DIRECTIONS AND IMPLICATIONS OF ADVANCED COMPUTING Seattle, Washington July 12, 1987 The adoption of current computing technology, and of technologies that seem likely to emerge in the near future, will have a significant impact on the military, on financial affairs, on privacy and civil liberty, on the medical and educational professions, and on commerce and business. The aim of the symposium is to consider these influences in a social and political context as well as a technical one. The social implications of current computing technology, particularly in artificial intelligence, are such that attempts to separate science and policy are unrealistic. We therefore solicit papers that directly address the wide range of ethical and moral questions that lie at the junction of science and policy. Within this broad context, we request papers that address the following particular topics. The scope of the topics includes, but is not limited to, the sub-topics listed. RESEARCH FUNDING DEFENSE APPLICATIONS - Sources of Research Funding - Machine Autonomy and the Conduct of War - Effects of Research Funding - Practical Limits to the Automation of War - Funding Alternatives - Can An Automated Defense System Make War Obsolete? COMPUTING IN A DEMOCRATIC SOCIETY COMPUTERS IN THE PUBLIC INTEREST - Community Access - Computing Access for Handicapped People - Computerized Voting - Resource Modeling - Civil Liberties - Arbitration and Conflict Resolution - Risks of the New Technology - Educational, Medical and Legal Software - Computing and the Future of Work Submissions will be read by members of the program committee, with the assistance of outside referees. The program committee includes Andrew Black (U. WA), Alan Borning (U. WA), Jonathan Jacky (U. WA), Nancy Leveson (UCI), Abbe Mowshowitz (CCNY), Herb Simon (CMU) and Terry Winograd (Stanford). Complete papers, not exceeding 6000 words, should include an abstract, and a heading indicating to which topic it relates. Papers related to AI and/or in-progress work will be favored. Submissions will be judged on clarity, insight, significance, and originality. Papers (3 copies) are due by April 1, 1987. Notices of acceptance or rejection will be mailed by May 1, 1987. Camera ready copy will be due by June 1, 1987. Proceedings will be distributed at the Symposium, and will be on sale during the 1987 AAAI conference. For further information contact Jonathan Jacky (206-548-4117) or Doug Schuler (206-783-0145). Sponsored by Computer Professionals for Social Responsibility P.O. Box 85481 Seattle, WA 98105 ------------------------------ Date: Tue 3 Mar 87 16:30:34-EST From: Gail E. Kaiser Subject: Conference - HICSS-21 Call For Papers CALL FOR PAPERS 21ST ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS-21) Papers are invited for the session(s) on Use of AI Techniques in Software Design and Implementation in the software track of the 21st annual Hawaii International Conference on System Sciences (HICSS-21), to be held in Kona, Hawaii next January 5-8, 1988. Topics of interest include, but are not limited to, the following artificial intelligence areas as they apply to software design and implementation, particularly for large-scale software systems. Techniques may apply to any or all phases of the software development process: project management, requirements, functional specification, design specification, modular decomposition, coding, integration, testing, maintenance, documentation, delivery, etc. Example applications are given in parentheses. - Automatic deduction (detecting inconsistencies among programmers' assumptions, automatic programming) - Knowledge representation (semantic nets, frames, etc. for representing programming information) - Learning (self-tuning of software tools to specific programs, generalization of program fragments to support reusability) - Natural language (matching functionality of program parts with the corresponding program documentation, explaining program components and their interactions to new project member) - Planning (detecting interactions among planned changes) - Rule-based systems (program transformation, performance tuning) - Search (retrieval of reusable program fragments) Six copies of the full paper (maximum 20 double-spaced pages) should be sent to the session chairman at the address given below. Papers must arrive by July 1, 1987. Authors will be notified of acceptance by September 7, 1987. Camera-ready copies will be due by October 19, 1987. Session chairman: Prof. Gail E. Kaiser, Columbia University, Department of Computer Science, New York, NY 10027. Phone: 212-280-3856. Electronic mail: kaiser@cs.columbia.edu, ...!columbia!cs!kaiser Software track chairman: Dr. Bruce D. Shriver, IBM T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY 10598. Phone: 914-789-7626. Electronic mail: shriver@ibm.com ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Thu Mar 5 18:02:25 1987 Date: Thu, 5 Mar 87 18:02:15 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #65 Status: R AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 65 Today's Topics: Queries - Frame+Rule-Based Systems & Case-Based Reasoning & Tracking Multiple Agents & AI Software on Intel-310 w/ Xenix & AML-V on RS-1 or RS-2, Reasoning - What is the Color of Clyde?, Methodology - Algorithm Description & Expert System Explanations, Philosophy - Consciousness, Seminar - AI from the Bottom Up (CMU) ---------------------------------------------------------------------- Date: Mon, 2 Mar 87 21:30 EST From: STREIFF%HARTFORD.BITNET@wiscvm.wisc.edu Subject: Frame+Rule Based Systems Hi, Im looking into writing a rule based expert system that uses frames for knowledge representation. It will be written in common lisp. Has anyone had any experience writing something of this nature? What are the advantages and drawbacks? Any help would be appreciated. Thank you. S. David Streiff Univ of Hartford West Hartford CT BitNet: STREIFF@HARTFORD.BITNET ------------------------------ Date: 4 Mar 87 19:12:46 GMT From: pulli@seismo.css.gov (Jay Pulli) Subject: case-based reasoning I am not a regular reader of this newsgroup and am thus unaware if this subject has been discussed at length. I am interested in finding some references on case based reasoning in ai. I'm interested in using it in conjunction with some signal characterization work I have been doing. Direct email to my address below would be greatly appreciated. Thanks in advance. /\ Jay J. Pulli / \ /\ Center for Seismic Studies _____/ \ / \ /\_____ Arlington, VA \ / \/ 703/276-7900 \/ pulli@seismo ------------------------------ Date: Mon, 2 Mar 87 12:18 EST From: DON%atc.bendix.com@RELAY.CS.NET Subject: Request for information I'm looking for references or discussions on associating observations with agents in multi-agent domains. My concern is not so much with determining the goodness of association as it is with controlling which associations are explored (i.e. controlling the search). In particular, consider a domain in which the particular agents are not known but the general types and proportions of each type are known. There is a fixed set of sensors for observing these agents. None of the sensors provides absolute identification nor continuous observation. There is some knowledge about the typical behaviors of the different types of agents. The reasoner's problem is, when presented with a new sensor report, to determine whether to associate the report with a new agent or with a previously observed agent. The problem quickly becomes one of controlling the search of previously observed agents in order to see which are most likely to be associated with the new report. I have some ideas about the search, but I'd like to see other published ideas or talk to those wiser than I before I expose myself. Thank you for any consideration. Don Mitchell Don@atc.bendix.com or Bendix Aero. Tech. Ctr. Don%atc.bendix.com@relay.cs.net 9140 Old Annapolis Rd. (301)964-4156 Columbia, MD 21045 ------------------------------ Date: 3 Mar 87 16:10:00 GMT From: hqda-ai!merlin@smoke.brl.mil (David S. Hayes) Subject: AI software on Intel-310 w/ Xenix We're looking for any AI or lisp software that runs on an Intel 310 under Xenix. We have some of these, and would like to start using them, but we don't know what sorts of things are available. Please provide then name of the product, a short description, the name of the vendor, and the vendor's phone number. Reply via e-mail, as I don't want to saturate these newsgroups. Thanks for the help, -- David S. Hayes, The Merlin of Avalon PhoneNet: (202) 694-6900 ARPA: merlin%hqda-ai.uucp@brl.arpa UUCP: ...!seismo!sundc!hqda-ai!merlin ------------------------------ Date: Mon, 2 Mar 87 10:38:31 PST From: John B. Nagle Subject: AML-V on RS-1 or RS-2? Is anyone running AML-V ("Gold Filling") on an IBM RS-1 (model 7510, model E CPU)? AML-V is a robot programming language. The RS-1 and RS-2 are IBM robots, impressive six-axis machines with force-sensing grippers. If you have an IBM disk pack, an RS-series robot probably built it. CMU, and MIT have RS-2 robots; Stanford has an RS-1, which was the pre-production model. IBM donated quite a number of these machines to various schools; these robots are more general-purpose than most manufacturing plants really need, but are excellent research tools. AML stands for A Manufacturing Language. AML-V is an experimental version developed at IBM's Yorktown Heights facility. Current work is on AML-X, which runs on an IBM PC/AT. AML-V was developed around 1985 and runs on the now-obsolete IBM Series I computers. The people who wrote AML-V are known to me but no longer have the Series I machines running that could build me the version I need. But such versions existed at one time, and if someone out there has one configured for an RS-1, it would be very valuable to me. The odds are excellent that someone who reads AILIST has an 8" floppy around that is just what I'm looking for. I'm working on a new approach to common-sense reasoning, one which involves the use of solid geometric modelling techniques to provide deep knowledge about the physical world. This leads naturally to robotic applications. One distinct advantage to working with robots, incidentally, is that the hype level is distinctly lower in the robotics community than in the rest of the AI world. Robotics people tend to shut up until they can demo. Is anyone running AML-V ("Gold Filling") on an IBM RS-1 (model 7510, model E CPU)? This usually runs on an RS-2, model 7565, with an model F CPU, but I'm trying to get it to run on an RS-1, which is supposedly possible. Is a different kernel required, or is it sufficient to put the configuration file on the boot floppy using the programs on the basic diagnostic diskette? I presently have the original RS-1 software installed (7505-AAA), but am upgrading to 7505-AAE ("Silver Lining 2 on 1") next week. 7505-AAA doesn't seem to recognize the AML-V distribution diskette as a valid volume. The tools for dealing with such problems are better in 7505-AAE, (the QVOLS command, for example) and I may be able to solve the problem then. But any advice from RS-1/RS-2 users would be appreciated. John Nagle Center for Design Research, Stanford. 415-856-0767. ------------------------------ Date: 2 Mar 87 10:15:57 GMT From: Dekang Lindek Reply-to: lindek@cs.strath.ac.uk (Dekang Lindek) Subject: What is the color of Clyde? Look, WORLD, here is a little default reasoning exercise: 95% of elephants have color grey. 40% of Royal Elephants have color yellow. Clyde is a Royal Elephant. The color of Clyde is likely to be: a) Grey b) Yellow c) Red d) Unknown Dekang Lin Dept. of CS Univ. of Strathclyde 26 Richmond Street Glasgow, G1 1XH, U.K. E-mail: ....!siesmo!mcvax!ukc!strath-cs!lindek ------------------------------ Date: Mon, 2 Mar 87 08:59 EST From: Seth Steinberg Subject: Re: Vulgar tongue Mr. Talmon misunderstood my argument. I did not come out against symbolic notation - I argued that mathematical and logical notation are not the appropriate symbolic notation for computer science. That is why I gave a series of examples showing that many fields have developed their own formalisms which are not variants of mathematical and logical notation. APL may look a lot like matrix algebra at first glance but it is decidedly procedural. Similarly, PROLOG may look like mathematical logic, but I don't recall Aristotle, Aquinas or Quine discussing anything even vaguely like 'cut'. I could base a programming language on chemical notation or architectural renderings, but understanding it would STILL require reasoning about procedural execution. Seth ------------------------------ Date: Wed, 4 Mar 87 08:08:46 est From: m06242%mwvm@mitre.ARPA Subject: Value of explanation facility in expert systems In considering the value of an explanation facility to an expert system, it is worthwhile to address the possible role of the system as a training facility. The student who follows the reasoning process is being led through the analytical structure devised by the systems builders. Since courtesy requires us to assume they chose a rational, efficient structure, the student can see an efficient approach to the problem. George Swetnam@MITRE "Cats elsewhere may be green, but the cats here don't care." -Kesh proverb * * George ------------------------------ Date: 2 Mar 87 10:55:00 EST From: "WHITE::PSOTKA" Reply-to: "WHITE::PSOTKA" Subject: RE: AIList Digest V5 #58 It seems to me that we generally have very clear criteria for consciousness (unlike much of the current discussion). We usually ask someone if they remember what happened: if they don't remember we tend to say they were unconscious. There are some general exceptions that prove this rule; namely, people do forget specific things but they generally know that they have forgotten: i.e., some fragmented memories still hang around to produce things like the Tip Of Tongue phenomenon where one knows one knows something but can't retrieve it. That kind of forgetting is clearly distinguished from being unconscious. On the whole there are two kinds of unconsciousness: when one is traumatized with a blow to the head, and when one is sleeping (either naturally or drug-induced). Football players provide everyday examples of the former: often after a violent blow someone stands beside a player asking him what he remembers. A few minutes later he is asked again. Usually when he remembers less the second time, he is pronounced to have a concussion and removed from the game for a while. Sometimes then, he has no recollection of having been asked the first time. Was he unconscious during that first interrogation even though he replied clearly and firmly? Well, on the whole I think that the event is strange and hard to categorize. My response seems to be, "Well, he didn't APPEAR to be unconscious, but I guess he was." It seems to fall into the same category as sleepwalking or talking in one's sleep. My speculative hunch about the topic is that consciousness produces memories because consciousness involves a wierd kind of multiplexing of a person's entire identity, the whole history of all existing memories, with the current percept, the current end segment of the stream of consciousness. There is an ongoing search and matching and resolution of all existing memories, plans, predicates, images, etc. with the current context. This seems to be necessary for awareness, recognition, inferences, etc. and it also somehow results in consciousness or IS consciousness. Let's get to work to find out how and why! ------------------------------ Date: 26 Feb 87 16:46:17 EST From: Marcella.Zaragoza@isl1.ri.cmu.edu Subject: Seminar - AI from the Bottom Up (CMU) AI SEMINAR TOPIC: "Artificial Intelligence from the Bottom Up" SPEAKER: Hans Moravec, Robotics WHEN: Tuesday, March 3, 1987, 3:30 pm WHERE: Wean Hall 5409 ABSTRACT Computers were created to do arithmetic faster and better than people. AI attempts to extend this superiority to other mental arenas. Some mental activities require little data, but others depend on voluminous knowledge of the world. Robotics was pursued in AI labs partly to automate the acquisition of world knowledge. It was soon noticed that the acquisition problem was less tractable than the mental activities it was to serve. While computers often exhibited adult level performance in difficult mental tasks, robotic controllers were incapable of matching even infantile perceptual skills. In hindsight the dichotomy is not surprising. Animal genomes have been engaged in a billion year arms race among themselves, with survival often awarded to the quickest to produce a correct action from inconclusive perceptions. We are all prodigous olympians in perceptual and motor areas, so good that we make the hard look easy. Abstract thought, on the other hand, is a small new trick, perhaps less than a hundred thousand years old, not yet mastered. It just looks hard when we do it. How hard and how easy? Average humans beings can be beaten at arithmetic by a one operation per second machine, in logic problems by 100 operations per second, at chess by 10,000 operations per second, in some narrow "expert systems" areas by a million operations. Robotic performance can not yet provide this same standard of comparison, but a calculation based on retinal processes and their computer visual equivalents suggests that 10 BILLION (10^10) operations per second are required to do the job of the retina, and a TRILLION (10^12) to match the bulk of the human brain. Truly expert human performance may depend on mapping a problem into structures originally constructed for perceptual and motor tasks - so it can be internally visualized, felt, heard or perhaps smelled and tasted. Such transformations give the trillion operations per second engine a purchase on the problem. The same perceptual-motor structures may also be the seat of "common sense", since they probably contain a powerful model of the world - developed to solve the merciless life and death problems of rapidly jumping to the right conclusion from the slightest sensory clues. Semilog plots of computer power hint that trillion operation per second computers will be common in twenty to forty years. Can we expect to program them to mimic the "hard" parts of human thought in the same way that current AI program capture some of the easy parts? It is unlikely that introspection of conscious thought can carry us very far - most of the brain is not instrumented for introspection, the neurons are occupied efficiently solving the problem at hand, as in the retina. Neurobiologists are providing some very helpful instrumentation extra-somatically, but not fast enough for the forty year timetable. Another approach is to attempt to parallel the evolution of animal nervous systems by seeking situations with selection criteria like those in their history. By solving similar incremental problems, we may be driven, step by step, through the same solutions (helped, where possible, by biological peeks at the "back of the book"). That animals started with small nervous systems gives confidence that small computers can emulate the intermediate steps, and mobile robots provide the natural external forms for recreating the evolutionary tests we must pass. By this "bottom up" route I hope one day to meet my "top down" colleagues half way. Together we can then metaphorically drive the golden spike that unites the two efforts. ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Thu Mar 5 18:02:50 1987 Date: Thu, 5 Mar 87 18:02:34 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #66 Status: R AIList Digest Thursday, 5 Mar 1987 Volume 5 : Issue 66 Today's Topics: Bibliography - Order Addresses & Definitions for AI.BIB4XC & Leff Bibliography AI.BIB49TR ---------------------------------------------------------------------- Date: Tue, 3 Mar 1987 16:36 CST From: Leff (Southern Methodist University) Subject: ORDER.ADDRESSES4 Publications Office Computer Science Division 573 Evans Hall, University of California Berkeley, California 94720 Department of Computer Science 405 Upson Hall Cornell University Ithaca, New York 14853 Department of Computer Science University of Missouri-Rolla 325 Math-C. Sc. Building Rolla, Missouri 65401 Technical Reports Department of Computer Science Oregon State Univeristy Corvallis, OR 97331 Center for Research on Information Systems Graduate School of Business Administration New York University 90 Trinity Place, Room 720 New York, NY 10006 no charge for single copies, additional copies $5.00 per additional copy Technical Report Facility James Lotkowski Department of Computer and Information Science School of Engineering and Applied Science University of Pennsylvania Philadelphia, PA 19104/D2 Boston University Computer Science Department 111 Cummington Street Boston, Mass 02215 Nancy Garrett Computer Science Department Indiana University Bloomington, Indiana 47405 Computer Science Department 226 Computer Science Building Iowa State University Ames, Iowa 50011-1040 Department of Computer Sciences Technical Report Center Taylor Hall 2.124 The University of Texas at Austin Austin, Texas 78712-1188 Arpanet Box CS.TECH@UTEXAS-20 Department of Computer Science University of New Hampshire Durham, New Hamshire MCC Technical Library Microelectornics and Computer Technology Corporation 3500 West Balcones Center Drive Austin, Texas 78759-6509 Technical Reports Computer Sciences Department University of Wisconsin 1210 West Dayton Street Madison, Wisconsin 53706 Department of Computer Science University of Illinois at Urbana-Champaign 1304 West Springfield Avenue Urbana, Illinois 61801 Stanford University Department of Computer Science Stanford, CA 94305-2140 (prepayment required, CA residents add tax) ------------------------------ Date: Tue, 3 Mar 1987 16:37 CST From: Leff (Southern Methodist University) Subject: DEFINITIONS FOR AI.BIB4XC D BOOK56 Advances in Automation and Robotics\ %V 1\ %I JAI Press\ %D 1985\ %C Greenwich, Connecticut D MAG93 COMPINT 85\ %D 1985 D MAG94 The Second Conference on Artificial Intelligence Applications\ %D 1985 D MAG95 Automation and Remote Control\ %V 47\ %N 2 Part 2\ %D FEB 1986 D BOOK57 Approximate Reasoning in Expert Systems\ %E Madan M. Gupta\ %E Abraham Kandel\ %E Wyllis Bandler\ %E Jerry B. Kiszka\ %I North Holland Publishing Co.\ %C Amsterdam-New York\ %D 1985 D BOOK58 Proceedings of the European Symposium on Programming held at the Univer sitat\ des Saarlandes,Saarbrucken, March 17-19 1986\ %E B. Robinet\ %E R. Willhelm\ %V 213\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1985 D MAG95 Soviet Journal of Computer and Systems Sciences\ %V 24\ %N 2\ %D MAR-APR 1986 D MAG96 Pattern Recognition Letters\ %V 4\ %N 3\ %D JUL 1986 D MAG97 Fuzzy Sets and Systems\ %V 20\ %N 2\ %D OCT 1986 D BOOK59 Artificial Intelligence and Man-Machine Systems\ %E H. Winter\ %V 80\ %S Lecture Notes in Control and Information Sciences\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1986 D BOOK60 Topics in the Theory of Computation (Borgholm, 1983)\ %V 102\ %S North-Holland Math. Stud.\ %I North Hold\ %C Amsterdam-New York\ %D 1985 D BOOK61 CAAP 86 (Nice, 1986)\ %V 214\ %I Springer-Verlag\ %C Berlin-Heidelberg-New York\ %D 1986 D MAG98 Electrical Communication\ %V 60\ %N 2\ %D 1986 D MAG99 SADHANA-Acad. Proc. Eng. Sci\ %V 9\ %D SEP 1986 D MAG100 Computer Vision, Graphics, and Image Processing\ %V 35\ %N 3\ %D SEP 1986 D MAG101 Computer Vision, Graphics and Image Processing\ %V 36\ %N 1\ %D OCT 1986 D MAG102 The Computer Journal\ %V 29\ %N 5\ %N 11\ %D OCT 1986 D MAG103 Le Travail Human\ %V 49\ %N 3\ %D SEP 1986 D MAG104 Image and Vision Computing\ %V 4\ %N 3\ %D AUG 1986 D MAG105 Computer Vision, Graphics and Image Processing\ %V 36\ %N 2-3\ %D NOV-DEC 1986 D MAG106 Pattern Recognition\ %V 19\ %N 6\ %D 1986 D BOOK62 Annual Review of Computer Science\ %I Annual Reviews Inc\ %C Palo Alto, CA\ %D 1986 D BOOK63 Proceedings of the Sixth International Conference on Robot Vision and\ Sensory Controls\ %I IFS Publications Limited\ %C Kempston\ %D 1986 ------------------------------ Date: Tue, 3 Mar 1987 16:36 CST From: Leff (Southern Methodist University) Subject: AI.BIB49TR %A Fil Fuma %A Erick Krotkov %A John Summers %T The Pennsylvania Active Camera System %I University of Pennsylvania %R MS-CIS-86-15 %K AI06 %A Tim Finin %A Aravind K. Joshi %A Bonnie Lynn Webber %T Natural Language Interactions with Artificial Experts %I University of Pennsylvania %R MS-CIS-86-16 %K AI01 AI02 O01 %A Dale A. Miller %A Gopalan Nadathur %T Higher-Order Logic Programming %I University of Pennsylvania %R MS-CIS-86-17 %K AI10 T02 %A Eric Krotkov %T Focusing %I University of Pennsylvania %R MS-CIS-86-22 %K AI06 %X automatic focusing of a computer controlled camera %A Rusena Bajcsy %A Eric Krotkov %A Max Mintz %T Models of Errors and Mistakes in Machine Perception %I University of Pennsylvania %R MS-CIS-86-26 %K AI06 stereo %A Aravind K. Joshi %A Bonnie L. Webber %A Ralph M. Weischedel %T Some Aspects of Default Reasoning in Interactive Discourse %I University of Pennsylvania %R MS-CIS-86-27 %K AI02 %A Yuen-Wah Eva Ma %A Ramesh Krishnamurti %A Bhagirath Narahari %A Dennis G. Shea %A Kwang-shi Shu %T High Performance Special-Purpose Computer Architectures for Robotics Applications %I University of Pennsylvania %R MS-CIS-86-28 %K H03 AI06 AI07 %A Dale A. Miller %A Gopalan Nadathur %T Some Uses of Higher Order Logic in Computational Linguistics %I University of Pennsylvania %R MS-CIS-86-31 %K AI10 AI02 %A Robert Rubinoff %T Adapting Mumble: Experience with Natural Language Generation %I University of Pennsylvania %R MS-CIS-86-32 %K text generation %K AI10 T02 %A Ethel Schuster %T Towards a Computational Model of Anaphora in Discourse: References to Events and Actions %R MS-CIS-86-34 %I University of Pennsylvania %K AI02 %A Tim Finin %A David Drager %T $GUMS sub 1$: A General User Modeling System %R MS-CIS-86-35 %I University of Pennsylvania %K AI08 O01 AA15 %A Robert Kass %A Ron Katriel %A Tim Finin %T Breaking the Primitive Concept Barrier %R MS-CIS-86-36 %I University of Pennsylvania %K AI16 KL-ONE %X describes extensions to KL-ONE %A Anthony S. Kroch %A Aravind K. Joshi %T Analyzing Extraposition in A Tree Adjoining Grammar %R MS-CIS-86-37 %I University of Pennsylvania %K AI02 %A Martha Elizabeth Pollack %T Inferring Domain Plans in Question-Answering %R MS-CIS-86-40 %I University of Pennsylvania %K AI08 O01 %A Brant A. Cheikes %T Research in Artificial Intelligence at the University of Pennsylvania %R MS-CIS-86-41 %I University of Pennsylvania %K AT09 AI16 %A Susan B. Davidson %A Mark M. Winkler %T Conflict Resolution in Class Conflict Graph Analysis %R MS-CIS-86-43 %I University of Pennsylvania %K conflict resolution AI16 %A Jean H. Gallier %A Stan Raatz %T Extending SLD-Resolution to Equational Horn Clauses Using E-Unification %I University of Pennsylvania %R MS-CIS-86-44 %K AI10 %A Dale Miller %A Amy Felty %T An Integration of Resolution and Natural Deduction Theorem Proving %I University of Pennsylvania %R MS-CIS-86-47 %K AI11 %A Sharon A. Stansfield %T A Rudimentary Active Multimodal, Intelligent System for Object Categorization %I University of Pennsylvania %R MS-CIS-86-48 %K AI06 %A Mark Turner %T Texture Discrimination by Gabor Functions %I University of Pennsylvania %R MS-CIS-86-51 %K AI06 %A Megumi Kameyama %T A Property-Sharing Constraint in Centering %I University of Pennsylvania %R MS-CIS-86-52 %K AI02 pronoun resolution %A Dale Miller %T A Theory of Modules for Logic Programming %I University of Pennsylvania %R MS-CIS-86-53 %K AI10 %A Claire Socolovsky Caine %T An Expert System for Marine Umbrella Liability Insurance Underwriting %I University of Pennsylvania %R MS-CIS-86-54 %K AA06 %A Gerald P. Stoloff %T Lanpick -- An Expert System for Recommendation of Local Area Network Hardware and Software Products %I University of Pennsylvania %R MS-CIS-86-55 %K AA08 %A Franc Solina %T Object Recognition Using Function Based Category Models %I University of Pennsylvania %R MS-CIS-86-56 %K AI06 %A Robert Kaas %T The Role of User Modelling in Intelligent Tutoring System %I University of Pennsylvania %R MS-CIS-86-58 %K AA07 AI08 %A Jean H. Gallier %A Stan Raatz %T Refutation Methods for Horn Clauses with Equality Based on Unification %I University of Pennsylvania %R MS-CIS-86-59 %K AI10 %A Megumi Kameyama %T Japanese Zero Pronominal Bindings: Where Syntax and Discourse Meet %I University of Pennsylvania %R MS-CIS-86-60 %K AI02 %A Robert Kaas %A Tim Finin %T The Role of User Models in Question Answering Systems %I University of Pennsylvania %R MS-CIS-86-63 %K AI01 AI08 personal investment AA06 %A Aravind K. Joshi %T An Introduction to Tree Adjoining Grammars %I University of Pennsylvania %R MS-CIS-86-64 %K AI06 AT08 %A Alex Pelin %A Jean Gallier %T Solving Word Problems in Free Algebras Using Complexity Functions %I University of Pennsylvania %R MS-CIS-86-65 %K AI11 %A Jugal Kalita %A Sunish Shende %T Generation of Natural Language Text Describing a System of Asynchronous, Concurrent Processes %I University of Pennsylvania %R MS-CIS-86-66 %A Hugh F. Durrant-Whyte %T Integration, Coordination and Control of Multi-Sensor Robot Systems %I University of Pennsylvania %R MS-CIS-86-67 %K AI06 AI07 blackboard AI01 %A Greg Hager %A Hugh F. Durrant-Whyte %T Information and Multi-Sensor Coordination %I University of Pennsylvania %R MS-CIS-86-68 %K AI07 AI06 H03 %A Tim Finin %T NFL- A Novices Frame Language %I University of Pennsylvania %R MS-CIS-86-71 %K AT18 T01 T03 %A Bonnie Lynn Webber %T Two Steps Closer to Event Reference %I University of Pennsylvania %R MS-CIS-86-74 %K AI02 AI16 %A Greg Hagar %T Active Reduction of Uncertainty in Multi-Sensor Systems %I University of Pennsylvania %R MS-CIS-86-76 %K H03 O04 %A Lokendra Shastri %T Massive Parallelism in Artificial Intelligence %I University of Pennsylvania %R MS-CIS-86-77 %K H03 %A Lokendra Shastri %A Raymond L. Wairous %T Learned Phonetic Discrimination Using Connectionistic Networks %I University of Pennsylvania %R MS-CIS-86-78 %K H03 AI05 %A Linda Ness %T Reducing Linear Recursion to Transitive Closure %I University of Texas at Austin, Department of Computer Sciences %R TR-86-25 %K AA09 AI10 %D NOV 1986 %X shows how to deal with a recursively expressed logic program that is designed to query a database %A David A. Schmidt %A Jacek Leszczylowski %T On Developing a Logic for Program Derivation and Verification %I Iowa State University Computer Science Department %R TR#86-16 %D NOV 1986 %K AA08 AI10 intuitionistic type theory predicate calculus %A James M. Bieman %A Albert L. Baker %A Paul M. Clites %A David A. Gustafson %A Austin C. Melton %T A Standard Representation of Imperative Language Programs %I Iowa Sate University Computer Science Department %R TR #86-17 %D NOV 1986 %K AA08 %A Ken-Chih Liu %A Rajshekhar Sunderraman %T Applying an Extended Relational Model to Indefinite Deductive Databases %I Iowa State University Computer Science Department %R TR #86-18 %D NOV 1986 %K AI10 AA09 %A Jacek Leszczylowski %A Jan Maluszynski %T Logic Programming with External Procedures: Introducing S-Unification %I Iowa State University Computer Science Department %R TR #86-21 %D DEC 1986 %K AI10 %A Chen %A Chi %A Ost %A Sabbaugh %A Spring %T Scheme Graphics Reference Manual %I Indiana University Computer Science Department %R TR 144 %D 1984 %K T01 %A Daniel P. Friedman %A Pee-Hong Chen %T Prototyping Data Flow by Translation Into Scheme %I Indiana University Computer Science Department %R TR 147 %D 1983 %K T01 %A Mitchell Wand %T A Semantic Algebra for Logic Programming %I Indiana University Computer Science Department %R TR 148 %D August 1983 %K AI10 %A Kent Dybvig %T C-Scheme Reference Manual %I Indiana University Computer Science Department %R TR 149 %D SEP 1983 %K T01 %A J. Barnden %T On Short-Term Information-Processing in Connectionist Theories %I Indiana University Computer Science Department %R TR 152 %D JAN 1984 %K H03 %A D. Friedman %A C. Hayes %A E. Kohlbecker %A M. Wand %T Scheme 84 Interim Reference Manual %R TR 153 %D JUN 1985 %I Indiana University Computer Science Department %K T01 %A E. Kohlbecker %T eu-Prolog: Reference Manual and Report %R TR 155 %D APR 1984 %I Indiana University Computer Science Department %K T02 %A C. D. Halpern %T An Implementation of 2-Lisp %R TR 160 %D JUN 1984 %I Indiana University Computer Science Department %K T01 %A L. D. Sabbagh %T Scheme as an Interactive Graphics Programming Environment %R TR 166 %D FEB 1985 %I Indiana University Computer Science Department %K T01 %A J. A. Barnden %T Representations of Intensions, Representations as Intensions, and Propositional Attitudes %R TR 172 %D JUN 1985 %I Indiana University Computer Science Department %K AI02 AI16 %A Johnathan Rees %A W. D. Clinger %T Revised Report on Scheme %R TR 174 %D AUG 1986 %I Indiana University Computer Science Department %K AI06 %$ 6.00 %A M. W. Lugowski %T Why Artificial Intelligence is Necessarily Ad Hoc: One's Thinking/Approach/ Model/Solution Rides on One's Metaphors %R TR 176 %D AUG 1985 %I Indiana University Computer Science Department %K AI16 %$ 2.00 %A S. C. Kwasny %A J. Dalby %A R. Port %T Rules for Automatic Mapping Between Fast and Slow Speech %R TR 175 %D JUL 1985 %I Indiana University Computer Science Department %K AI05 %A Matthias Felleisen %T Transliterating Prolog into Scheme %R TR 182 %D OCT 1985 %I Indiana University Computer Science Department %K T01 T02 %A Christopher T. Haynes %T Logic Continuations %R TR 183 %D NOV 1985 %I Indiana University Computer Science Department %K AI10 %A John A. Barnden %T Imputations and Explications: Representational Problems in Treatments of Propositional Attitudes %R TR 187 %D JAN 1986 %I Indiana University Computer Science Department %K AI16 %A Erich J. Smythe %T The Pleasures of SINN: A System for Programming Connectionist Models %R TR189 %D FEB 1986 %I Indiana University Computer Science Department %K FEB 1986 %A Matthias Felleisen %A Daniel P. Friedman %T Control Operators, the SECD-Machine and the $lambda$-calculus %R TR 197 %D JUN 1986 %I Indiana University Computer Science Department %K T01 %A Eugene E. Kohlbecker %T Syntactic Extensions in the Programming Language Lisp %R TR 199 %D AUG 1986 %I Indiana University Computer Science Department %K T01 %$ 12.00 (Ph. D. Dissertation) %A Matthias Felleisen %T A Final Scheme-Word on Landin's J-Operator %R TR 205 %D NOV 1986 %I Indiana University Computer Science Department %K T01 %A Bipin Indurykha %T Analogies and Metaphors: An Interdisciplinary Perspective %R BUCS Tech Report #86-012 %D DEC 1986 %I Boston University Department of Computer Science %K AI08 AI16 AI02 %A Michael Siegel %T Automatic Rule Derivation for Semantic Query Optimization %R BUCS Tech Report #86-013 %D DEC 1986 %I Boston University Computer Science Department %K AA09 AI01 %A Leonard Uhr %T Toward a Computational Information-Processing Model of Object Perception %I University of Wisconsin-Madison, Computer Sciences Department %R TR651 %D JUL 1986 %K AI08 AI06 %X describes what is known and is necessary for development of a model of visual perception in humans as well as those points of information that are lacking. %A Matthew J. Thazhuthaveetil %T A Structured Memory Access Architecture for LISP %I University of Wisconsin-Madison, Computer Sciences Department %R TR658 %D AUG 1986 %K H02 T01 %A Udi Manber %T Using Mathematical Induction to Design Computer Algorithms %I University of Wisconsin-Madison, Computer Sciences Department %R TR660 %D AUG 1986 %K AA08 AI11 %A M. A. Sridhar %T Efficient Algorithms for Multiple Pattern Matching %I University of Wisconsin-Madison, Computer Sciences Department %R TR661 %D AUG 1986 %K O06 %A Charles V. Steward %A Charles R. Dyer %T A Scheduling Algorithm for the Pipelined Image-Processing Engine %I University of Wisconsin-Madison, Computer Sciences Department %R TR664 %D SEP 1986 %K AI06 H03 %A Nian Li %A Leonard Uhr %T Comparative Timings for a Neuron Recognition Program on Serial and Pyramid Computers %I University of Wisconsin-Madison, Computer Sciences Department %R TR665 %D SEP 1986 %K AA10 AI06 H03 %X a system to recognize neurons in photomicrographs %A Gilbert Verghese %A Shekhar Mehta %A Charles R. Dyer %T Image Processing Algorithms for the Pipelined Image-Processing Engine %I University of Wisconsin-Madison, Computer Sciences Department %R TR668 %D SEP 1986 %K local peak detection median filtering thinning Hough transform photometric stereo AI06 O06 H03 %A Mitali Bhattacharyya %A David Cohrs %A Barton Miller %T Implementation of a Visual UNIX Process Connector %I University of Wisconsin-Madison, Computer Sciences Department %R TR677 %D DEC 1986 %X An environment for connecting several UNIX processes. Not specifically AI related %A Ze-Nian Li %A Leonard Uhr %T Pyramid Vision Using Key Features to Integrate Image-Driven Bottom-Up and Model-Driven Top Down Processes %I University of Wisconsin-Madison, Computer Sciences Department %D DEC 1986 %R TR678 %K H03 AI06 %A Charles R. Dyer %T Multiscale Image Understanding %I University of Wisconsin-Madison, Computer Sciences Department %R TR679 %D DEC 1986 %K texture AI06 %A G. T. Toussaint %T Computational Geometry and Morphology %I McGill University, School of Computer Science %R TR-SOCS-86.3 %D FEB 1986 %K AA10 AI06 O06 %X applications of such algorithms as hulls, medial axis, geodesic and visibility for polygons to understanding biological shape and shape change. %A R. De Mori %A L. Lam %A M. Gilloux %T Learning and Plan Refinement in a Knowledge-Based System for Automatic Speech Recognition %R TR-SOCS-86.14 %I McGill University, School of Computer Science %D MAY 1986 %K AI09 AI04 AI05 %X experimental work on recognition of connected letters by 100 speakers %A Heedong Ko %A Kunwoo Lee %T Toward a Practical Planning System for Assembly Tasks %R Department of Computer Science File 957 %I University of Illinois at Urbana-Champaign %D SEP 1986 %K AA26 %A Carl Thomas Uhrik %T A Rule Exerciser for Knowledge Base Enhancement in Expert Systems %R Department of Computer Science File 969 %I University of Illinois at Urbana-Champaign %D SEP 1986 %K AI01 O04 AA23 AA10 %X The system has been applied to soybean diagnosis and monkey behavior discrimination %A Kenneth D. Forbus %A Dedre Gentner %T Learning Physical Domains: Toward a Theoretical Framework %R Department of Computer Science File 1247 %I University of Illinois at Urbana-Champaign %D DEC 1986 %K AI08 AI04 %A Steven Greenbaum %T Input Transformations and Resolution Implementation Techniques for Theorem Proving in First-Order Logic %R Department of Computer Science File 1298 %I University of Illinois at Urbana-Champaign %D SEP 1986 %K AI11 %X the aim is opposed to solve small sized problem with little or no human guidance as opposed to other systems which are designed to solve large problems with human guidance. Uses priority-based search strategy, discrimination networks and Knuth-Bendix method %A Brian Falkenhainer %T An Examination of the Third State in the Analogy Process: Verification- Based Analogical Learning %R Department of Computer Science File 1302 %I University of Illinois at Urbana-Champaign %D OCT 1986 %K AI04 qualitative models liquid flow and heat flow %A Y-L. Steve %A Daniel D. Gajski %T LES: A Layout Expert System %R Department of Computer Science File 1308 %I University of Illinois at Urbana-Champaign %D NOV 1986 %K AA04 %X A layout system that is competitive with human designers %A Krish Purswani %A Larry Rendell %T A Probabilistic Reasoning-Based Approach to Machine Learning %R Department of Computer Science File 1311 %I University of Illinois at Urbana-Champaign %D DEC 1986 %K AI03 O04 %A Yoram Ofer Moses %T Knowledge in a Distributed Environment %D MAR 1986 %R STAN-CS-86-1120 %I Stanford University Computer Science %K H03 %X Discusses the effects of unreliable communications on coordination of an expert system, the Byzantine agreement problem and the "cheating wives" puzzle .br br 15.00 104 pages %A Glenn Douglas Rennels %T A Computational Model of Reasoning from the Clinical Literature %D JUN 1986 %I Stanford University Computer Science %R STAN-CS-86-1122 %K AA01 AI01 %X discusses getting information from the clinical literature into an AI system for patient care. Example problem is "breast cancer management options." .br br 244 pages 15.00 %A H. Penny Nii %T Blackboard Systems %D JUN 1986 %I Stanford University Computer Science %R STAN-CS-86-1123 %X general review of black board systems .br br 86 pages, 10.00 %A Daniel J. Scales %T Efficient Matching Algorithms for the SOAR/OPS5 Production System %D JUN 1986 %I Stanford University Computer Science %R STAN-CS-86-1124 %K T03 AI01 %X 50 pages 10.00 %A Eric Schoen %T The CAOS System %D MAR 1986 %I Stanford University Computer Science %R STAN-CS-86-1125 %K H03 O03 %X a real time Lisp distributed system for signal interpretations .br br 69 pages 10.00 %A Byron Davies %T CAREL: A Visible Distributed Lisp %D MAR 1986 %R STAN-CS-86-1126 %I Stanford University Computer Science %K H02 H03 T01 %X A system programming language that runs on the TI Explorer that includes real time display of the processor activity and data communications; useful as an educational tool .br br 15 pages 5.00 %A Yonathan Malachi %T A Timely Resolution %D MAR 1986 %R STAN-CS-86-1127 %I Stanford University Computer Science %K AI11 AI10 T01 T02 H03 TABLOG unification %X 15.00 145 pages %A Evan R. Cohn %A Ramsey W. Haddad %T Beta Operations: Efficient Implementation of a Primitive Parallel Operation %D AUG 1986 %R STAN-CS-86-1129 %I Stanford University Computer Science %K H03 %X The Beta Operation can be performed in O(log N + log **2 M) time on a hypercube where N is the size of the input and M is the size of the output. .br br 5.00, 18 pages %A Vishvjit S. Nalwa %A Thomas O. Binford %T On Detecting Edges %R STAN-CS-86-1130 %D MAR 1986 %I Stanford University Computer Science %K AI06 %X Proposed method will localize edges to within a thilrd of a pixel if step-size over noise ratio > 2.5 .br br 50 pages 10.00 %A Yehoshua Sagiv %T Optimizing Datalog Programs %R STAN-CS-86-1132 %D MAR 1986 %I Stanford University Computer Science %K AI10 %X Prolog programs without function symbols are optimized. Also defines a new form of equivalence under which such programs can be compared. .br br 30 pages, 50.00 %A Richard James Treitel %T Sequentialization of Logic Programs %R STAN-CS-86-1135 %D NOV 1986 %I Stanford University Computer Science %K AI10 %X 16 pages 15.00 %A Harold Brown %A Erich Schoen %A Bruce Delogi %T An Experiment in Knowledge-based Signal Understanding Using Parallel Architectures %R STAN-CS-86-1136 %D OCT 1986 %I Stanford University Computer Science %K H03 AA18 T01 %X System was tested on radar emissions from air craft .br br 36 pages 5.00 ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 7 11:59:04 1987 Date: Sat, 7 Mar 87 11:58:33 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #67 Status: R AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 67 Today's Topics: Bibliography - Leff AI.BIB48TR ---------------------------------------------------------------------- Date: Tue, 3 Mar 1987 16:36 CST From: Leff (Southern Methodist University) Subject: AI.BIB48TR %R AI-013-85 %T The LRC Machine Translation System %I Microelectronics and Computer Technology Corporation %D MAR 1985 %K AI02 %R AI-012-85 %T A Machine-Aided Translation Bibliography %I Microelectronics and Computer Technology Corporation %D MAR 1985 %K AT09 AI02 %R AI-011-85 %T A Survey of Machine Translation: Its History, Current Status and Future Prospects %I Microelectronics and Computer Technology Corporation %D MAY 1985 %K AI02 AT08 %R AI-010-85 %T Machine Translation: Viewpoint From Both Sides %I Microelectronics and Computer Technology Corporation %D FEB 1985 %K AI02 %R AI-009-85 %T Machine Translation %I Microelectronics and Computer Technology Corporation %D FEB 1985 %K AI02 %R AI-008-85 %T A Practical Comparison of Parsing Strategies %I Microelectronics and Computer Technology Corporation %D MAY 1985 %K AI02 %R AI-007-85 %T Parser Construction Techniques: A Tutorial %I Microelectronics and Computer Technology Corporation %D MAY 1985 %K AI02 AT08 %R AI-006-85 %T Transportability to Other Languages: The Natural Language Processing Project in the AI Program at MCC %I Microelectronics and Computer Technology Corporation %D MAR 1985 %K AI02 %R AI-0100-05 %T Using Explicit Contradictions to Provide Explanations in a TMS %I Microelectronics and Computer Technology Corporation %D APR 1985 %K AI15 %R AI/CAD-162-85 %T Analogical Reasoning for Digital System Synthesis %I Microelectronics and Computer Technology Corporation %D MAY 1986 %K AA04 %R DB-081-86 %T A Computational Logic for Database Programs %I Microelectronics and Computer Technology Corporation %D March 12, 1986 %K AA09 %R DB-064-86 %T Analyzing the Run-Time Behavior of Logic Programs %I Microelectronics and Computer Technology Corporation %D March 6, 1986 %K AI10 %R DB-058-86 %T Some extensions to the Closed World Assumption in Databases %I Microelectronics and Computer Technology Corporation %D March 3, 1986 %K AA09 AI16 %R DB-026-86 %T LDL: A Logic Based Data-Language %I Microelectronics and Computer Technology Corporation %D February 11, 1986 %K AI10 AA09 %R DB-021-86 %T Optimizing the Rule/Data Interface in a Knowledge Management System %I Microelectronics and Computer Technology Corporation %D February 3, 1986 %K AA09 AI01 %R DB-171-85 %T Tools for the Analysis of Large Prolog Programs %I Microelectronics and Computer Technology Corporation %D DEC 3, 1985 %K T02 O02 %R DB-132-85 %T Parallel Evaluation of Recursive Rule Queries %I Microelectronics and Computer Technology Corporation %D October 1985 %K AI01 %R DB-121-85 %T Magic Sets and Other Strange Ways to Implement Logic Programs %I Microelectronics and Computer Technology Corporation %D October 28, 1985 %K AI10 %R DB-101-85 %T On the Implementation of a Simple Class of Logic Queries for Databases %I Microelectronics and Computer Technology Corporation %D October 14, 1985 %K AI10 AA09 %R DB-088-85 %T Safety and Compilation of Non-Recursive Horn Clauses %I Microelectronics and Computer Technology Corporation %D September 20, 1985 %K AI10 %R DB-038-85 %T Object Oriented Database Systems and Knowledge Systems %I Microelectronics and Computer Technology Corporation %D July 9, 1985 %K AI16 %R DB-021-85 %T A Logic-Programming/Object-Oriented Cocktail %I Microelectronics and Computer Technology Corporation %D September 10, 1985 %K AI10 %R Mcc/db/dbsa-7/rev.0 %T Database and Knowledge Based System Opportunities %I Microelectronics and Computer Technology Corporation %D October 5, 1986 %K AA09 %R mcc/db/kbs-77/rev.1 %T The Representation and Deductive Retrieval of Complex Objects %I Microelectronics and Computer Technology Corporation %D May 6, 1985 %K AI16 %R mcc/db/kbs-75/rev.1 %T The Transition from Data Management to Knowledge Management %I Microelectronics and Computer Technology Corporation %D April 30, 1985 %K AI16 %R mcc/db/kbs-52/rev.1 %T Opportunities for Parallelism in Knowledge Management Systems: A Bibliography %I Microelectronics and Computer Technology Corporation %D December 11, 1984 %K AT09 H03 %R mcc/db/kbs-49/rev.1 %T Logic Programming/Database Interfaces %I Microelectronics and Computer Technology Corporation %D December 5, 1984 %K AA09 AI10 %R mcc/db/kbs-44/rev.1 %T Rule Support in Prolog %I Microelectronics and Computer Technology Corporation %D November 30, 1984 %K AI01 T02 %R mcc/db/kbs-43/rev.1 %T Logics for Semantic Data Models %I Microelectronics and Computer Technology Corporation %D November 30, 1984 %K AI10 AI16 %R mcc/db/kbs-33/rev.0 %T KBS Requirements, Rev.0 %I Microelectronics and Computer Technology Corporation %D October 31, 1984 %K AI16 %R mcc/db/kbs-29/rev.1 %T Knowledge Base Development and Use in Deductive Data Management %I Microelectronics and Computer Technology Corporation %D October 31, 1984 %K AI16 %R HI-294-86 %T Human Computer Interactions and Intelligent Tutoring Systems %I Microelectronics and Computer Technology Corporation %D September 8, 1986 %K AA07 O01 %R HI-200-86 %T Speech Processing for the User Interface %I Microelectronics and Computer Technology Corporation %D July 1986 %K AI05 %R HI-179-86 %T A Parser for Portable NL Interfaces Using Graph-Unification-Based Grammars %I Microelectronics and Computer Technology Corporation %D June 1986 %K AI02 %R HI-075-86 %T Parsing as Heuristic Graph Search %I Microelectronics and Computer Technology Corporation %D Mar 6, 1986 %K AI02 %R HI-073-86 %T Ambiguity and Procrastination in NL Interfaces %I Microelectronics and Computer Technology Corporation %D March 1986 %K AI02 %R HI-012-86 %T Some Properties of Combinatory Categorical Grammars of Relevance to Parsing %I Microelectronics and Computer Technology Corporation %D January 22, 1986 %K AI02 %R HI-017-86 %T A General User Model, Part 1: Connectionist Framework %I Microelectronics and Computer Technology Corporation %D January 31, 1986 %K AI08 %R HI-118-85 %T Extraposition from NP as Anaphora %I Microelectronics and Computer Technology Corporation %D October 23, 1985; revision one: March 1986 %K AI02 %R HI-111-85 %T Memory for Spatial Locations and Related Topics: A Review and Annotated Bibliography %I Microelectronics and Computer Technology Corporation %D October 18, 1985 %K AI08 AT09 %R HI-089-85 %T Graphic Interfaces for Knowledge-Based System Development %I Microelectronics and Computer Technology Corporation %D September 1985; revision one: December 1985 %K O01 O02 %R HI-084-85 %T Analysis of User-Expert Dialogues: Task Networks, Subdialogue Boundary Markers and Antecedent Distribution %I Microelectronics and Computer Technology Corporation %D December 1, 1985 %K AI08 AI01 AI02 %R HI-074-85 %T Natural Language Understanding: How Natural Can it Be? %I Microelectronics and Computer Technology Corporation %D September 13, 1985 %K AI02 %R HI-066-85 %T Applications of Speech Technology in the CAD Workstation %I Microelectronics and Computer Technology Corporation %D April 26, 1985 %K AI05 AA04 AA15 %R HI-85-103-04 %T On the Applied Use of Computer Models of Human Memory: A Proposal for a Large-Scale Personal Filing System %I Microelectronics and Computer Technology Corporation %D 1985 %K AA14 AI08 %R HI-85-102-04 %T Memory Structure, Focusing, and Anaphora Resolutions: A Study and Comparison of Computer and Human Memory %I Microelectronics and Computer Technology Corporation %D 1985 %K AI08 %R HI-85-100-04 %T Speech Processing State of the Art Report %I Microelectronics and Computer Technology Corporation %D 1985 %K AI05 AT08 %R HI/STP-054-86 %T Artificial Intelligence and Advanced User Interfaces %I Microelectronics and Computer Technology Corporation %D February 25, 1986 %K AI02 %R PP-083-86 %T Goal Scheduling and Memory Management in Parallel Logic Systems %I Microelectronics and Computer Technology Corporation %D March 15, 1986 %K H03 AI10 %R PP-020-86 %T Potentials for Parallel Execution of Common Lisp Programs %I Microelectronics and Computer Technology Corporation %D January 30, 1986 %K T01 H03 %R PP-154-85 %T An Abstract Machine for Restricted And-Parallel Execution of Logic Programs %I Microelectronics and Computer Technology Corporation %D November 26, 1985 %K AI10 H03 %R PP-140-85 %T A Study of the Parallelism Inherent in Combinator Reduction %I Microelectronics and Computer Technology Corporation %D Nov 11, 1985 %K H03 %R PP-104-85 %T A Restricted and-Parallel Execution Model and Abstract Machine for Prolog Programs %I Microelectronics and Computer Technology Corporation %D October 2, 1985 %K T02 H03 %R PP-079-85 %T Parallel Execution of a Rule-Based Expert System %I Microelectronics and Computer Technology Corporation %D 1985 %K AI01 H03 %R PP-024-85 %T Expert System Application Study %I Microelectronics and Computer Technology Corporation %D 1985 %K AI01 %R PP-019-85 %T Proceedings of the MCC Workshop on LFP (Logical/Functional) programming Languages %I Microelectronics and Computer Technology Corporation %D July 1, 1985 %K AI10 %R STP-053-86 %T Biggertalk* = Biggertalk + Gordion %I Microelectronics and Computer Technology Corporation %D November 1, 1985 %K AI10 %R TR 86-1 %T Data and Resource Abstraction Mechanisms on an Object-Based Architecture %A Kanad Gose %A R. M. Steward %I Iowa State University %D JAN 1986 %R TR 86-16 %T On Developing a Logic for Program Derivation and Verification %A David A. Schmidt %A Jacek Leszczylowski %I Iowa State University %D NOV 1986 %K AA08 AI10 predicate calculation %R TR 86-21 %T Logic Programming with External Procedures: Introducing S-Unification %A Jacek Lesczylowski %A Jan Maluszynski %I Iowa Sate University %D DEC 1986 %K AI10 %R 83-5 %A Helen M. Gigley %A Jean-Francois Boulicaut %A Eric Ramahefarivony %T Grasper-Insa -- A Graph Processing Tool for Knowledge Engineering %I University of New Hamshire %D SEP 1983 %K T01 %R 83-6 %A Helen M. Gigley %T Processing Word Ambiguities: Availability of Multiple Meanings of Ambiguous Words in Aphasic Patients and Normal Controls %I University of New Hampshire, Department of Computer Science %D SEP 1983 %K AA08 AA11 AI02 %R 83-8 %A Sylvia Weber Russell %T Conceptual Analysis of Partial Metaphor %I University of New Hampshire, Department of Computer Science %D OCT 1983 %K AI02 %R 83-9 %A Michael J. Quinn %T On the Speedup of Parallel Depth-First Branch-and-Bound Algorithms %I University of New Hampshire, Department of Computer Science %D NOV 1983 %K H03 AI03 %R 84-13 %A Eugene C. Freuder %T Utilizing Subgraph Isomorphism in Constraint Graphs %I University of New Hampshire, Department of Computer Science %D JAN 1984 %K constraint satisfaction AI03 %R 84-14 %A Eugene C. Freuder %T A Sufficient Condition for Backtrack-Bounded Search %I University of New Hampshire, Department of Computer Science %D JAN 1984 %K AI03 constraint satisfaction %R 84-15 %A Eugene C. Freuder %T Direct Independence of Variables in Constraint Satisfaction Problems %I University of New Hampshire, Department of Computer Science %D MAR 1984 %K AI03 H03 %A Lee Tibbert %A R. Daniel Bergeron %R 84-18 %T Graphics Programming For Knowledge-Guided Interaction %I University of New Hampshire, Department of Computer Science %D JAN 1984 %K O01 %A Eugene C. Freuder %A Michael J. Quinn %T Taking Advantage of Stable Sets of Variables in Constraint Satisfaction Problems %R 84-20 %I University of New Hampshire, Department of Computer Science %D DEC 1984 %K AI03 %A Eugene C. Freuder %A Michael J. Quinn %T Parallelism in an Algorithm that Takes Advantage of Stable Sets of Variables to Solve Constraint Satisfaction Problems %R 85-21 %I University of New Hampshire, Department of Computer Science %D Jan 1985 %K AI03 H03 %A Michael J. Quinn %A Narsingh Deo %R 85-23 %T An Upper Bound for the Speedup of Parallel Branch-and-Bound Algorithms %I University of New Hampshire, Department of Computer Science %D FEB 1985 %K AI03 H03 %A Helen M. Gigley %T Computational Neurolinguistics -- What is it all About %R 85-24 %I University of New Hampshire, Department of Computer Science %D JAN 1985 %K AI08 AI02 %A Helen M. Gigley %T Grammar Viewed as a Functioning Part of a Cognitive System %R 85-25 %I University of New Hampshire, Department of Computer Science %D JAN 1985 %K AI02 AI08 %A Helen M. Gigley %T Computational Neurolinguistic Modelling Integrating 'Natural Computation' Control with Performance Defined Representatives %R 85-26 %I University of New Hampshire, Department of Computer Science %D SEP 1985 %K AI02 AI08 HOPE %A Michael J. Quinn %A Narsingh Deo %T An Upper Bound for the Speedup of Parallel Best-Bound Branch-and-Bound Algorithms %R 85-27 %I University of New Hampshire, Department of Computer Science %D SEP 1985 %K AI03 H03 %A Helen M. Gigley %T Studies in Artificial Aphasia - Experiments in Processing Change %R 85-28 %I University of New Hampshire, Department of Computer Science %D OCT 1985 %K AI08 AA11 AI02 %A Bruce Barker %T An Abstract Prolog Machine %R 85-29 %I University of New Hampshire, Department of Computer Science %D DEC 1985 %K H02 T02 Warren %A Henk J. Haarmann %A Helen M. Gigley %T Neural-like Modelling of Synchronization Deficits in Aphasic Comprehension %R 86-32 %I University of New Hampshire, Department of Computer Science %D MAR 1986 %K AI02 AA11 AI08 %A Eugene C. Freuder %T Applying Constraint Satisfaction Search Techniques to Concept Learning %R 86-33 %I University of New Hampshire, Department of Computer Science %D MAR 1986 %K AI03 AI04 %A Brian Otis %A Eugene C. Freuder %T Subdivision of Knowledge for Igneous Rock Identifications %R 86-35 %I University of New Hampshire, Department of Computer Science %D APR 1986 %K AI01 AA03 %A Sylvia Weber Russell %R 86-36 %T A Perspective from Computer Analysis %I University of New Hampshire, Department of Computer Science %D APR 1986 %K metaphor AI02 %A Helen M. Gigley %R 86-36 %T Lexical Ambiguity Resolution in Aphasia %I University of New Hampshire, Department of Computer Science %D MAY 1986 %K AA11 AI02 %A Helen M. Gigley %T Sentence Comprehension Processing - A Serial ORder, Time-Synchronous Process %R 86-39 %I University of New Hampshire, Department of Computer Science %D APR 1986 %K AI02 HOPE %A Michael J. Quinn %T Implementing Best-First Branch-And-Bound Algorithms on Hypercube Multiprocessors %R PCL 86-02 %I University of New Hampshire, Parallel Computing Laboratory, Department of Computer Science %D SEP 1986 %K AI02 H03 %A Saul Gorn %T Who Can Be Replaced by A Computer %R MS-CIS-85-04 %I University of Pennsylvania %K O05 %A Saul Gorn %T Self-Annihilating Sentences: Saul Gorn's Compendium of Rarely Used Cliches %R MS-CIS-85-03 %I University of Pennsylvania %K AI02 %A Robert Ruminoff %T Explaining Concepts in Expert Systems: The Clear System %R MS-CIS-85-06 %I University of Pennsylvania %K O01 AI01 %A Vijay-Shankar %A Aravind Joshi %T Some Computational Properties of Tree Adjoining Grammars %R MS-CIS-85-07 %I University of Pennsylvania %K AI02 %A D. Smitley %A S. M. Goldwasser %A I. Lee %T IPON - Advanced Architectural Framework for Image %R MS-CIS-85-13 %I University of Pennsylvania %K AI06 H03 MIMD %A Eric P. Krotkov %T Results in Finding Edges and Corners in Images Using the First Directional Derivative %R MS-CIS-85-14 %I University of Pennsylvania %K AI06 %A Anthony S. Kroch %A Aravand K. Joshi %T The Linguistic Relevance of Tree Adjoining Grammars %R MS-CIS-85-16 %I University of Pennsylvania %K AI02 %A Dale A. Miller %A Gopalan Nadathur %T A Computational Logic Approach to Syntax and Semantics %R MS-CIS-85-17 %I University of Pennsylvania %K AI10 AI11 %A Paul A. Fishwick %T Hierarchical Reasoning: Simulating Complex Processes over Multiple Levels of Abstraction [Dissertation Exam Version] %R MS-CIS-85-21 %I University of Pennsylvania %K simulation %A Aravind K. Joshi %T Tree Adjoining Grammars: How Much Context-Sensitivity is Required to Provide Reasonable Structural Descriptions %R MS-CIS-85-23 %I University of Pennsylvania %K AI02 %A David Smiley %T The Design and Analysis of a Stereo Vision Algorithm %R MS-CIS-85-27 %I University of Pennsylvania %K AI06 %A Peter Allen %A Ruzena Bajcsy %T Two Sensors Are Better Than One: Examples of Integration of Vision and Touch %R MS-CIS-85-29 %I University of Pennsylvania %K AI06 AI07 %A Samuel Goldwasser %A Ruzena Bacsy %T A Distributed Active Sensor Processor System %R MS-CIS-85-30 %I University of Pennsylvania %K AI06 AI07 AI01 %A Franc Solina %T Errors in Stereo Due to Quantization %R MS-CIS-85-34 %I University of Pennsylvania %K AI06 %A David A. Klein %T An Expert Systems Approach to Realtime, Active Management of a Target Resource %R MS-CIS-85-40 %I University of Pennsylvania %K AI01 AA08 YES/MVS IBM O03 %X (describes part of a system for monitoring IBM systems) %A Robin F. Karlin %T Romper Mumble %R MS-CIS-85-41 %I University of Pennsylvania %K text generation %A Brant A. Cheikes %T Monitor Offers an a Dynamic Database [sic]: The Search for Relevance %R MS-CIS-85-43 %I University of Pennsylvania %K AA09 %A Aravind K. Joshi %T Grammar, Phrase Structure %R MS-CIS-85-45 %I University of Pennsylvania %K AI02 %A Ethel Shuster %T Code Switching in Yiddish and Spanish: Evidence for the Translation Model %R MS-CIS-85-49 %I University of Pennsylvania %K AI02 AI08 %X discusses second-language acquisition %A Bonnie Lynn Webber %T Question, Answer and Responses: Interacting with Knowledge Base Systems %R MS-CIS-85-50 %I University of Pennsylvania %K O01 %A Paul A. Fishwick %T Hires: Hierarchical Reasoning System %R MS-CIS-85-52 %I University of Pennsylvania %K simulation %X manual for system %A A. Zwarico %A I. Lee %T Proving a Network of Real-Time Processes Correct %R MS-CIS-85-53 %I University of Pennsylvania %K AA08 %A Ruzena Bajcsy %T Active Perception vs. Passive Perception %R MS-CIS-85-54 %I University of Pennsylvania %K AI06 AI16 %X getting a system to "look" as opposed to just "see." %A Greogry Donald Hager %T Computational Aspects of Proofs in Modal Logic %R MS-CIS-85-55 %I University of Pennsylvania %K AI10 %A Kathleen Filliben McCoy %T Correcting Object-Related Misconceptions %R MS-CIS-85-57 %I University of Pennsylvania %K AI08 AI01 %X discusses how human experts correct misconceptions as they use the ROMPER system %A Peter Kirby Allen %T Object Recognition Using Vision %R MS-CIS-85-60 %I University of Pennsylvania %K AI06 AI07 %X includes discussion of the use of vision and exploratory tactile sensing in object recognition %A Aravind K. Joshi %A K. Vijay-Shanker %A David J. Weir %R MS-CIS-86-01 %T The Relationship Between Tree Adjoining Grammars and Head Grammars %I University of Pennsylvania %K AI02 %A Hossam A. Elgindy %T Efficient Algorithms for Computing the Weak Visibility Polygon from an Edge %I University of Pennsylvania %R MS-CIS-86-04 %K O06 %A Jean H. Gallier %T A Fast Algorithm for Testing Unsatisfiability of Ground Horn Clauses with Equations %I University of Pennsylvania %R MS-CIS-86-06 %K AI10 %A Richard Paul %A Hugh F. Durrant-Whyte %A Max Mintz %T A Robust, Distributed Sensor and Actuation Robot Control System %I University of Pennsylvania %R MS-CIS-86-07 %K AI06 AI07 %X proposal for a blackboard based robot system %A Hugh F. Durrant-Whyte %T Consistent Integration and Propagation of Disparate Sensor Observations %I University of Pennsylvania %R MS-CIS-86-08 %K AI07 AI06 %A Eric P. Krotkov %A Jean-Paul Maritan %T Range From Focus %I University of Pennsylvania %R MS-CIS-86-09 %K AI07 AI06 %A Jean H. Gallier %A Stan Raatz %T Hornlog: A Graph Based Interpreter for General Horn Clauses %I University of Pennsylvania %R MS-CIS-86-10 %K AI10 %A Stan Raatz %A George Drastal %T Relating Expert System Rule Interactions to Norms of Rule-based Programming %I University of Pennsylvania %R MS-CIS-86-12 %K AI01 %A Ruzena Bajcsy %A Max Mintz %A Erica Liebman %T A Common Framework for Edge Detection and Region Growing %I University of Pennsylvania %R MS-CIS-86-13 %K AI06 ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 7 11:59:43 1987 Date: Sat, 7 Mar 87 11:59:31 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #68 Status: R AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 68 Today's Topics: Bibliogrpahy - Leff AI.BIB43TR ---------------------------------------------------------------------- Date: Tue, 3 Mar 1987 16:35 CST From: Leff (Southern Methodist University) Subject: AI.BIB43TR %A Ashar A. Butt %T Cell Design in Prolog %I University of California, Berkeley %R CSD 86/286 %K AA04 T02 %X $3.50 %A David Michael Ungar %T The Design and Evaluation of a High Performance Smalltalk System %I University of California, Berkeley %R CSD 86/287 %X $9.00 %A Yigal Arens %T CLUSTER: An Approach to Contextual Language Understanding %I University of California, Berkeley %R CSD 86/293 %K Unix Consultant AI02 AA15 %X $8.25 %A Robert Wilensky %T Some Problems and Proposals for Knowledge Representation %I University of California, Berkeley %R CSD 86/294 %K AI02 AI16 kodiak AT14 %X $3.25 %A Joseph Pasquale %T Knowledge Based Distributed System Management %I University of California, Berkeley %R CSD 86/295 %K AA08 %X $2.50 %A Paul Schafran Jacobs %T A Knowledge Based Approach to Language Production %I University of California, Berkeley %R CSD 86/254 %K AI02 O01 %X $7.50 %A Jung-Herng Chang %T High Performance Execution of Prolog Programs Based on a Static Data Dependence Analysis %I University of California, Berkeley %R CSD 86/263 %K T02 %X $5.00 %R CS-86-147 Computer Science Department %I Washington State University %C Pullman, WA 99164-1210 %T COREL - A CONCEPTUAL RETRIEVAL SYSTEM %A M. Kathryn Di Benigno %A George R. Cross %A Gary G. deBessonet %K AI16 %X Corel is an experimental retrieval system that employs techniques of artificial intelligence. Articles of the Civil Code of Louisiana have been conceptually indexed using frame-based knowledge structures in hope of improving accessibility over traditional key-word retrieval systems. A set of macro packages has been developed to allow a domain expert to implement a retrieval system based on this methodology. %R CS-86-149 Computer Science Department %I Washington State University %C Pullman, WA 99164-1210 %T THE STRUCTURE OF CCLIPS %A Mohammed Nasiruddin %A George R. Cross %A Cary G. deBessonet %K AA24 %X The Civil Code Legal Information Processing System (CCLIPS) is a conceptual retrieval system whose domain is the Louisiana Civil Code. Statutes are coded in Atomically Normalized Form (ANF) and entered into a database. Legal situations are entered by the user in ANF and relevant statutes are retrieved. We discuss the current status of the system and some plans for further development. %R CSL T.R. 86-291 %T Lisp and Prolog Memory Performance %A Evan Tick %D January 1986 %I Stanford University Computer Systems Laboratory %X This report presents a comparison between a Lisp and Prolog architecture bas ed on memory performance. Four Lisp programs were translated into Common Lisp and Prolog abstract machine instruction sets. The translated programs were emulated and memory reference counts collected. Memory usage statistics indicate how the two languages do fundamental computations different ways with varying efficiency. Additional measurements of production systems running on a conventional host are presented. %R CSL-TN-86-286 %T Microprogram Control of a Prolog Machine %A Kiyomi Koyama %D January 1986 %X .br br A Prolog machine design and its control are described. The machine features two-stage pipelining, a triple bus interconnection data path and support for concurrent control of micro-operations. The objective of this design is to improve execution of a Prolog processor by simultaneously performing multiple micro-operations. Capabilities of concurrent operation support are described in detail and demonstrated using some example Prolog functions. Two-stage pipeline technique as applied to non-deterministic control of Prolog program execution will be presented. .br br 37 pages.....$4.35 %R 1260 %T The AQ15 Inductive Learning System: An Overview and Experiments %A R. S. Michalski %A I. Mozetic %A J. Hong %A N. Lavrac %I The University of Illinois at Urbana-Champaign, Department of Computer Scienc e %D JUL 1986 %K AI04 %R 1268 %T Automated Reference Librarians for Program Libraries and Their Interaction with Language Based Editors %A J. J. Shilling %I The University of Illinois at Urbana-Champaign, Department of Computer Scienc e %D AUG 1986 %K AA14 %R 1293 %T Induction, Of and By Probability %A Larry Rendell %R 1268 %I The University of Illinois at Urbana-Champaign, Department of Computer Scienc e %D AUG 1986 %K AI04 %A Marianne Winslett Wilkins %T A Model-Theoretic Approach to Updating Logical Databases %D JAN 1986 %R STAN-CS-86-1096 %I Stanford University, Department of Computer Science %D JAN 1986 %K AI10 AA09 %$ 5.00 %A Jitendra Malik %T Interpreting Line Drawings of Curved Objects %D DEC 1985 %R STAN-CS-86-1099 %I Stanford University, Department of Computer Science %K AI06 %$ 15.00 %A Martin Abadi %A Zohar Manna %T Modal Theorem Proving %D MAY 1986 %R STAN-CS-86-1100 %I Stanford University, Department of Computer Science %K AA13 AI11 %$ 5.00 %A David E. Foulser %T On Random Strings and Sequence Comparisons %D FEB 1986 %R STAN-CS-86-1101 %I Stanford University, Department of Computer Science %K O06 %$ microfiche only charge listed as N/A %A Devika Subramanian %T A Survey of AI Classnotes for Winter 84-85 %D APR 1986 %R STAN-CS-86-1104 %I Stanford University, Department of Computer Science %K AI16 %$ 15.00 %A Martin Abadi %A Zohar Manna %T A Timely Resolution %D APR 1986 %R STAN-CS-86-1106 %I Stanford University, Department of Computer Science %K AI11 temporal logic AI10 %A David E. Smith %T Controlling Inference %D APR 1986 %R STAN-CS-86-1107 %I Stanford University, Department of Computer Science %K AI03 %$ 15.00 %A K. Morris %A J. Ullman %A A. Van Gelder %T Design Overview of the NAIL! System %D MAY 1986 %R STAN-CS-86-1108 %I Stanford University, Department of Computer Science %K AI10 AA09 %X Nail = Not another implementation of logic %$ 5.00 %A Ross Casley %T A Proof Editor for Propositional Temporal Logic %D MAY 1986 %R STAN-CS-86-1109 %I Stanford University, Department of Computer Science %K AI11 %$ 5.00 %A Y. Malachi %A Z. Manna %A R. Waldinger %T TABLOG: A New Approach to Logic Programming %D MAR 1985 %I Stanford University, Department of Computer Science %R STAN-CS-86-1110 %K AI10 %$ 5.00 %A Paul Rosenbloom %A John Laird %T Mapping Explanation-Based Generalization onto Soar %D JUN 1986 %R STAN-CS-86-1111 %I Stanford University, Department of Computer Science %K AI16 explanation-based generalization %$ 5.00 %A Jeffrey F. Naughton %T Optimizing Function-Free Recursive Inference Rules %D MAY 1986 %R STAN-CS-86-1114 %I Stanford University, Department of Computer Science %K AI10 %$ 5.00 %A B. G. Buchanan %A B. Hayes-Roth %A O. Lichtarge %T The Heuristic Refinement Method for Deriving Solution Structures of Proteins %R STAN-CS-86-1115 %D MAR 1986 %I Stanford University, Department of Computer Science %K AA10 AI01 %$ 5.00 %A Li-Min Fu %A Bruce G. Buchanan %T Inductive Knowledge Acquisition for Rule-based Expert Systems %R STAN-CS-86-1116 %I Stanford University, Department of Computer Science %D OCT 1985 %K AI01 %$ 5.00 %A D. Howe %T Implementing Number Theory: An Experiment with NUPRL %I Cornell University, Department of Computer Science %D MAY 1986 %R 86-752 %K AA13 AI11 AI14 %A J. Sasaki %T Extracting Efficient Code From Constructive Proofs %I Cornell University, Department of Computer Science %D JUNE 1986 %R 86-757 %K AA08 %A M. P. Mendler %T First and Second Lambda Calculi with Recursive Types %I Cornell University, Department of Computer Science %D JUL 1986 %R 86-764 %K T01 %A J. Bates %T THEFRL Mathematics Environment: A Knowledge Based Medium %I Cornell University, Department of Computer Science %D AUG 1986 %R 86-768 %K AA13 %A C. Kreitz %T Constructive Automata Theory Implemented with the Nuprl Proofl Development Systems %I Cornell University, Department of Computer Science %D SEP 1986 %R 86-779 %K AA13 AA08 AI11 %A A. Moitra %A P. Panangaden %T A Proof System for Dataflow Networks with Indeterminate Modules %I Cornell University, Department of Computer Science %D SEP 1986 %R 86-782 %K AA13 AA08 AI11 %A J. D. Ward %A B. E. Gillett %A A. R. DeKock %T CIGEN: A System for Testing Knowledge Base Compilation Heuristics on a Microcomputer %I University of Missouri-Rolla Department of Computer Science %R CSC 84-10 %D 1984 %K AA08 %A K. W. Whiting %A A. R. DeKock %A J. B. Prater %T A Focus of Attention Algorithm for Expert Systems %I University of Missouri-Rolla Department of Computer Science %R CSC 84-12 %D 1984 %K AI01 %A R. M. Butler %A A. R. DeKock %T An Algorithm for Parallel Subsumption %I University of Missouri-Rolla Department of Computer Science %R CSc 84-1 %D 1985 %K H03 AI11 %A R. L.Boehning %A B. E. Gillett %T A Parallel Branch and Bound Algorithm for Integer Linear Programming Models %I University of Missouri-Rolla Department of Computer Science %R CSC 85-2 %D 1985 %K H03 AI03 %A R. S. Dare %A A. R. DeKock %T Genesis of an Expert System for UMR Degree Auditing %I University of Missouri-Rolla Department of Computer Science %R CSC 86-3 %D 1986 %K AI01 AA07 %A J. H. Marchal %A A. R. DeKock %T MICA: prototyping an Expert System Consultant %I University of Missouri-Rolla Department of Computer Science %R CSC 86-5 %D 1986 %K AI01 %A J. A. Vila Ruiz %A A. R. DeKock %T A Computerized Audio-Visual Speech Model %I University of Missouri-Rolla Department of Computer Science %R CSC 86-4 %D 1986 %K AI05 %A D. Wise %T The Applicative Style of Programming %I Oregon State University, Department of Computer Science %R CSTR 84-2 %D 1984 %A F. Springsteel %T Expert Systems for Exploratory Data Analysis: Towards Automated Research %I Oregon State University, Department of Computer Science %R CSTR 85-30-1 %D 1985 %K AA12 AI01 automated knowledge acquisition %A F. Springsteel %T Biomedical Knowledge Acquisition: Three Systems Reviewed %I Oregon State University, Department of Computer Science %R CSTR-86-60-1 %D 1986 %K AA01 AI01 AA12 automated knowledge acquisition %A T. Dietterich %T Learning at the Knowledge Level %I Oregon State University, Department of Computer Science %R CSTR-86-30-1 %D 1986 %K AI04 %A T. G. Dietterich %A N. S. Flann %A D. C. Wilkins %T A Summary of Machine Learning Papers from IJCAI-85 %I Oregon State University, Department of Computer Science %R CSTR-86-30-2 %D 1986 %K AI04 %A N. S. Flann %A T. G. Dietterich %T Two Short Papers on Machine Learning %I Oregon State University, Department of Computer Science %R CSTR-86-30-3 %D 1986 %K AI04 %A A. Birjandi %A T. G. Lewis %T YASHAR: A Ruled Based Meta-tool for Program Development %I Oregon State University, Department of Computer Science %R CSTR-86-10-1 %D 1986 %K AI01 AA08 %X this system does computer language to language translations and restructuring of code %A A. Birjandi %A T. G. Lewis %T ARASH: A Re-Structuring Environment for Building Software Systems >From Reusable Components %I Oregon State University, Department of Computer Science %R CSTR-86-10-2 %D 1986 %K AA08 %A A. Birjandi %A T. G. Lewis %T Artimis: A Module Indexing and Source Program Reading and Understanding Environment %I Oregon State University, Department of Computer Science %R CSTR-86-10-3 %D 1986 %K AA14 AA08 %A J. S. Bennett %A T. G. Dietterich %T The Test Incorporation Hypothesis and the Weak Methods %I Oregon State University, Department of Computer Science %R CSTR-86-30-4 %D 1986 %K AI03 %A N. S. Flann %A T. G. Dietterich %T Selecting Appropriate Representations for Learning From Examples %I Oregon State University, Department of Computer Science %D 1986 %R CSTR-86-30-5 %K AI16 AI04 %A C. S. Rapp %T Algebra READER: An Expert Algebra Work Problem Reader %I Oregon State University, Department of Computer Science %D 1986 %R CSTR-86-30-6 %K AA07 AA13 AI02 AI01 %A W. S. Bregar %A A. M. Farley %A G. Bayley %T Knowledge Sources for an Intelligent Algebra Tutor %I Oregon State University, Department of Computer Science %R CSTR-86-30-7 %D 1986 %K AA07 AA13 %A C. Swart %A D. Richards %T On the Inference of Strategies %I Oregon State University, Department of Computer Science %R CSTR-86-20-3 %D 1986 %K AI04 O06 %A W. G. Rudd %A K. Uppuluri %A G. R. Cross %A S. Haley %T Expert Systems for Management of Pests of Agricultural Crops %I Oregon State University, Department of Computer Science %R CSTR-86-60-4 %D 1986 %K AA23 AI01 %A T. G. Dietterich %A D. G. Ullman %T FORLOG: A Logic-based Architecture for Design %I Oregon State University, Department of Computer Science %R CSTR-86-30-8 %D 1986 %K AA05 AI10 %A D. G. Ullman %A L. A. Stauffer %A T. G. Dietterich %T Preliminary Results of an Experimental Study of the Mechanical Design Process %I Oregon State University, Department of Computer Science %R CSTR-86-30-9 %D 1986 %K AA05 AI08 %A Edward A. Stohr %A Jon A. Turner %A Yannis Vassiliou %A Norman H. White %T Research in Natural Language Retrieval Systems %I New York University, Center for Research on Information Systems %R 30 %K AA09 AI02 %A Jon A. Turner %A Matthias Jarke %A Edward A. Stohr %A Yannis Vassiliou %A Norman H. White %T Using Restricted Natural Language for Data Retrieval: A Plan for Field Evalua tion %I New York University, Center for Research on Information Systems %R 38 %K AA09 AI02 %A Yannis Vassiliou %A James Clifford %A Matthias Jarke %T How Does an Expert System Get its Data? %I New York University, Center for Research on Information Systems %R 50 %K AI01 %A Matthias Jarke %A Jacob Shalev %T A Knowledge-Based Approach to the 'Analysis and Design of Business Transactio n Processing Systems %I New York University, Center for Research on Information Systems %R 53 %K AA09 AA06 %A Yannis Vassiliou %A Matthias Jarke %A Edward A. Stohr %A Jon A. Turner %A Norman H. White %T Natural Languages for Database Queries: A Laboratory Study %I New York University, Center for Research on Information Systems %R 55 %K AI02 AA09 %A Matthias Jarke %A Yannis Vassiliou %T Coupling Expert Systems with Database Management Systems %I New York University, Center for Research on Information Systems %R 54 %K AI01 AA09 %A James Clifford %A Matthias Jarke %A Yannis Vassiliou %T A Short Introduction to Expert Systems %I New York University, Center for Research on Information Systems %R 59 %K AI01 AT08 %A Matthias Jarke %A Jon A. Turner %A Edward A. Stohr %A Yannis Vassiliou %A Norman H. White %A Ken Michielsen %T A Field Evaluation of Natural Language for Data Retrieval %I New York University, Center for Research on Information Systems %R 62 %K AI02 AA09 %A Matthias Jarke %A James Clifford %A Yannis Vassiliou %T An Optimizing Prolog Front End to a Relational Query Systems %I New York University, Center for Research on Information Systems %R 65 %K AA09 T02 %A Taracad Sivasankaran %A Matthias Jarke %T Logic-Based Formula Management Strategies in an Actuarial Consulting System %I New York University, Center for Research on Information Systems %R 69 %K AA06 AA12 AI01 %A Matthias Jarke %A Jurgen Krause %A Yannis Vassiliou %T Studies in the Evaluation of a Domain-Independent Natural Language Query Syst em %I New York University, Center for Research on Information Systems %R 72 %K AI02 AA09 %A Yannis Vassiliou %A Jim Clifford %A Matthias Jarke %T Database Access Requirements of Knowledge Based Systems %I New York University, Center for Research on Information Systems %R 74 %K AA09 %A Matthias Jarke %T External Semantic Query Simplification: A Graph Theoretic Approach and its Implementation in Prolog %I New York University, Center for Research on Information Systems %R 75 %K AA09 T02 %A Vasant Dhar %A Casey Quayle %T An Approach to Dependency Directed Backtracking Using Domain Specific Knowled ge %I New York University, Center for Research on Information Systems %R 89 %K AI03 %A Vasant Dhar %T On the Plausibility and Scope of Expert Systems in Management %I New York University, Center for Research on Information Systems %R 98 %K AI01 AA06 %A James Clifford %A Matthias Jarke %A Henry C. Lucas %T Designing Expert Systems in a Business Environment %I New York University, Center for Research on Information Systems %R 99 %K AI01 %A Vasant Dhar %A Matthias Jarke %T Analogical and Dependency-Directed Reasoning Strategies for Large Systems Evolution %I New York University, Center for Research on Information Systems %R 100 %K AI16 %A Jae B. Lee %A Edward A. Stohr %T Representing Knowledge for Portfolio Management Decision Making %I New York University, Center for Research on Information Systems %R 101 %K AA06 AI01 AI13 %R AI-208-86 %T Some Thoughts on Proof Discovery %I Microelectronics and Computer Technology Corporation %D JUN 1986 %K AI16 %R AI-160-86 %T Models of Technology Transfer at MCC %I Microelectronics and Computer Technology Corporation %D MAY 1986 %K AT19 %R AI-159-86 %T A Man-Machine Procedure for Building a Medium Sized Knowledge Base by Analogy and Learning: Preliminary Report %I Microelectronics and Computer Technology Corporation %D MAY 1986 %K AI16 AI04 %R Ai-158-86 %T The Use of Analogy in Automatic Proof Discovery: Preliminary Report %I Microelectronics and Computer Technology Corporation %D MAY 1986 %K AI16 %R AI-157-86 %T Algorithms for Subpixel Registration %I Microelectronics and Computer Technology Corporation %D APR 1986 %K AI06 %R AI-102-86 %T Extended Contradiction Resolution %I Microelectronics and Computer Technology Corporation %D MAR 1986 %K AI16 %R AI-101-86 %T Expert Systems in the Marketplace %I Microelectronics and Computer Technology Corporation %D MAR 1986 %K AI01 %R AI-082-86 %T Automating Knowledge Acquisition From Experts %I Microelectronics and Computer Technology Corporation %D MAR 1986 %K AI01 %R AI-016-86 %T A Diffusing Computation for Truth Maintenance %I Microelectronics and Computer Technology Corporation %D 1985 %K AI15 %R AI-013-86 %T Rule-Based Geometrical Reasoning for the Interpretation of Line Drawings %I Microelectronics and Computer Technology Corporation %D JAN 24, 1986 %K AI01 AI06 %R AI-181-85 %T Efficient Management of Backtracking in And-Parallelism %I Microelectronics and Computer Technology Corporation %D DEC 12, 1985 %K AI10 H03 AI03 %R AI-119-85 %T A Knowledge Engineering Bibliography %I Microelectronics and Computer Technology Corporation %D NOV 1985 %K AI01 AT09 %R AI-109-85 %T An Encoding Technique for the Efficient Implementation of Type Inheritance %I Microelectronics and Computer Technology Corporation %D DEC 1985 %K O06 %R AI-100-85 %T Suggested Reading List for an Introduction to Artificial Intelligence %I Microelectronics and Computer Technology Corporation %D OCT 1985 %K AT09 AI16 %R AI-083-85 %T Machine Translation: An American Perspective %I Microelectronics and Computer Technology Corporation %D AUG 1985 %K AI02 GA02 %R AI-082-85 %T Integrating Data Type Inheritance into Logic Programming %I Microelectronics and Computer Technology Corporation %D AUG 1985 %K AI10 %R AI-076-85 %T Logic and Inheritance %I Microelectronics and Computer Technology Corporation %D JUL 1985 %K AI10 %R AI-068-85 %T LOGIN: A Logic Programming Language with Built-In Inheritance %I Microelectronics and Computer Technology Corporation %D JUL 1985 %K AI10 %R AI-062-85 %T An Algorithm for Truth Maintenance %I Microelectronics and Computer Technology Corporation %D APR 1985 %K AI15 %R AI-055-85 %T CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks %I Microelectronics and Computer Technology Corporation %D JUL 15, 1985 %K AI16 %R AI-054-85 %T "I Had A Dream" AAAI Presidential Address %I Microelectronics and Computer Technology Corporation %D AUG 19, 1985 %K AI16 %R AI-017-85 %T Extraction of Expert System Rules From Text %I Microelectronics and Computer Technology Corporation %D JUN 1985 %K AI01 AI02 %R Ai-015-85 %T The Treatment of Grammatical Categories and Word Order in Machine Translation %I Microelectronics and Computer Technology Corporation %D MAR 1985 %K AI02 %R AI-014-85 %T An Evaluation of Metal: The LRC Machine Translation System %I Microelectronics and Computer Technology Corporation %D MAR 1985 %K AI02 ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 7 11:58:35 1987 Date: Sat, 7 Mar 87 11:58:15 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #69 Status: R AIList Digest Friday, 6 Mar 1987 Volume 5 : Issue 69 Today's Topics: Bibliography - Leff AI.BIB47C ---------------------------------------------------------------------- Date: Tue, 3 Mar 1987 16:36 CST From: Leff (Southern Methodist University) Subject: AI.BIB47C %A D. W. Murray %A A. Kashko %A H. Buxton %T A Parallel Approach to the Picture Restoration Algorithm of Geman and Geman on an SIMD Machine %J MAG104 %P 133-142 %K AI06 H03 %A M. A. Sutton %A Mingqi Cheng %A W. H. Peters %A Y. J. Chao %A S. R. McNeill %T Application of an Optimized Digital Correlation Method to Planar Deformation Analysis %J MAG104 %P 143-150 %K AI06 %A H. S. Ranganath %T Hardware Implementation of Image Registration Algorithms %J MAG104 %P 151-158 %K AI06 %A J. R. T. Lewis %A T. Sopwith %T Three-dimensional Surface Measurement by Microcomputer %J MAG104 %P 159-166 %K AI06 H01 %A S. Sitharama Iyengar %A Stephan W. Miller %T Efficient Algorithm for Polygon Overlay for Dense Map Image Data Sets %J MAG104 %P 167 %K AI06 O06 %A Ron Bauman %A Tom A. Turano %T Production Based Language Simulation of Petri Nets %J Simulation %V 47 %N 5 %D NOV 1986 %P 191-198 %K AA08 AI01 %A P. Dubois %T Artificial Intelligence and Living Logic (French) %J Cybernetica %V 29 %N 3 %D 1986 %P 175-192 %K AI16 %A Sabah U. Randhawa %A William J. Barton Jr. %A Salahuddin Faruqui %T Wavesolder Assistant: An Expert System to Aid Troubleshooting of the Wave Soldering Process %J Computers and Industrial Engineering %V 10 %N 4 %P 325-334 %K AA26 AA05 %A Martien J. Quaak %A Frans Westerman %A Jan A. Schouten %A Arie Hasman %A Jan H. van Bemmel %T Appraisal of Computerized Medical Histories: Comparisons between Computerized and Conventional Records %J Computers and Biomedical Research %V 19 %N 6 %P 551-564 %D DEC 1986 %K AA01 %A Lawrence O. Hall %A Sue Szabo %A Abraham Kandel %T On the Derivation of Memberships for Fuzzy Sets in Expert Systems %J Information Sciences %V 40 %N 1 %D NOV 1986 %P 39-52 %K AI01 O04 %A R. A. Aliyev %A A. E. Tserkovnyy %T An Intelligent Robot for Quality Estimation and Sorting of Components for Automated Quality Control %J Soviet Journal of Computer and Systems Sciences %V 24 %N 3 %D MAY-JUN 1986 %P 113-119 %K AI07 %A D. A. Pospelov %A I. Ya. Sil'dmyae %T Role Structures in the in the Representation of Knowledge and in Interactive Systems %J Soviet Journal of Computer and Systems Sciences %V 24 %N 3 %D MAY-JUN 1986 %P 53-58 %K AI16 %A A. P. Guminskiy %A V. V. Martynov %T Construction and Implementation of a Scheduling Algorithm in a Calculus Based on Universal Semantic Code %J Soviet Journal of Computer and Systems Sciences %V 24 %N 3 %D MAY-JUN 1986 %P 48-52 %K AI07 %A Ye. I. Yefimov %T Calculation of Probability in Fuzzy Human Interface %J Soviet Journal of Computer and Systems Sciences %V 24 %N 3 %D MAY-JUN 1986 %P 34-47 %K AI07 %A Thomas Jupille %T Expert Systems are New Textbooks %J Research and Development %V 28 %N 12 %D DEC 1986 %P 52-58 %K AI01 AT08 %A Jorge G. Moser %T Integration of Artificial Intelligence and Simulation in a Comprehensive Decision Support System %J Simulation %V 47 %N 6 %P 223-232 %K AI13 %A E. Hisdal %T Infinite-Valued Logic Based on Two-Valued Logic and Probability. Part 1.2 Different Sources of Fuzziness %J International Journal of Man-Machine Studies %V 25 %N 2 %D AUG 1986 %P 113-138 %K O04 %A K. L. Norman %A L. J. Weldon %A B. Schneiderman %T Cognitive Layouts of Windows and Multiple Screens for User Interfaces %J International Journal of Man-Maachine Studies %V 25 %N 2 %D AUG 1986 %P 229 %K AA15 AI08 %A Su-Shing Chen %A Michael Penna %T Shape and Motion of Nonrigid Bodies %J MAG105 %P 175-207 %K AI06 %A Chew L. Tan %A W. N. Martin %T A Distributed System for Analyzing Time-Varying Multiresolution Imagery %J MAG105 %P 162-174 %K AI06 H03 %A Muralidhara Subbarao %A Allen M. Waxman %T Closed Form Solutions to Image Flow Equations for Planar Surfaces in Motion %J MAG105 %P 208-228 %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 %J MAG105 %P 229-255 %K AI06 %A C. H. Chien %A J. K. Aggarwal %T Identification of 3D Objects from Multiple Silhouettes Using Quadtrees/ Octrees %J MAG105 %P 256-273 %K AI06 %A Prasanna G. Mulgaonkar %A Linda G. Shapiro %A Robert M. Haralick %T Shape from Perspective: A Rule-Based Approach %J MAG105 %P 298-320 %K AI06 AI01 %A Vincent Shang-Shouq Hwang %A Larry S. Davis %A Takashi Matsuyama %T Hypothesis Integration in Image Understanding Systems %J MAG105 %P 321-371 %K AI06 %A Robert M. Haralick %T Computer Vision Theory: The Lack Thereof %J MAG105 %P 372-386 %K AI06 AI16 %A J. Stojanovski %T A Note on Implementing Prolog in Lisp %J Information Processing Letters %V 23 %N 5 %D NOV 24 1986 %P 261-264 %K T01 T02 %A R. A. King %T Expert Systems for Material Selection and Corrosion %J The Chemical Engineer (London) %N 431 %D DEC 1986 %P 42-45 %K AA05 AI01 %A J. Mantas %T An Overview of Character Recognition Methodologies %J MAG106 %P 425-430 %K AI06 %A J. Cerella %T Pigeons and Perceptrons %J MAG106 %P 431-438 %K AI06 AI08 AA10 %A A. Goshtasby %T Piecewise Linear Mapping Functions for Image Registration %J MAG106 %P 459-466 %K AI06 %A J. N. Kapur %T Application of Entropic Measures of Stochastic Dependence on Pattern Recognition %J MAG106 %P 473-476 %K AI06 %A M. A. Ismail %A S. Z. Selim %T Fuzzy c-means: Optimality of Solutions and Effective Termination of the Algorithm %J MAG106 %P 481 %K O04 O06 %A A. J. P. Theuwissen %A C. H. L. Weitjins %T The Accordian Imager, A New Solid State Image Sensor %J Philips Technical Review %P 1-9 %V 43 %N 1-2 %K AI06 %A A. D. Goldfinger %A G. M. Oderda %A R. F. Wachter %T IPECAC: An Expert System for the Management of Poisoning Incidents %J John Hopkins APL Technical Digest %V 7 %N 4 %D OCT-DEC 1986 %P 372-378 %K AI01 AA01 %A Andrew Russell %T Vision System Based on a Single-chip Microcomputer %J Microprocessors and Microsystems %V 10 %N 9 %D NOV 1986 %P 485-490 %K H01 AI06 %X describes an image processing system based on an 8751 microcontroller with a Dynamic Ram as a vision sensor %A Min De Cheng %A Xie Chang Shen %A Min Qiang Zhou %A Quing Yun Shi %A Min Ping Qian %T Introduction to Pattern Recognition %I Shanghai Kexu Jishu Chubanshe %C Shanghai %D 1983 %K AT15 AI06 %X in Chinese %A A. I. Degtyarev %A A. A. Voronkov %T Methods of Control of Equality in Mechanical Proofs of Theorems %J Kibernetika (Kiev) %V 1986 %N 3 %P 34-41 %K AI11 AI03 %A Francois Fages %A Gerard Huet %T Complete Sets of Unifiers and Matchers in Equational Theories %J Theoretical Computer Science %V 43 %N 2-3 %P 189-200 %K AI11 %A N. V. Gogoberidze %A Sh. G. Mgeladze %T An Approach to the Problem of Automation of Logical Inference %J Soobshch. Akad. Nauk Gruzin SSR %V 119 %D 1985 %N 3 %P 581-584 %K AI11 %X Russian. English and Georgian Summaries %A Jan Grabowski %T Unificational Dynamic Logic %J Elektron. Informationsverarb. Kybernet. %V 22 %D 1986 %N 5-6 %P 325-338 %K AI11 %A Ryszard Jakubowski %T A Structural Representation of Shape and Its Features %J Inform. Sci %V 39 %D 1986 %N 2 %P 129-151 %K AI06 AI16 %A V. I. Vasil'ev %A F. P. Ovsyannikova %T Learning Pattern Recognition with a Given Reliability %J Kibernetika (Kiev) %V 1986 %N 3 %P 50-56 %K AI06 AI04 %A P. Ecsedi-Toth %T On the Expressive Power of Equality-Free First Order Languages %J Z. Math. Logik Grundlag. Math %V 32 %D 1986 %N 4 %P 371-375 %A V. K. Kabulov %T Proof of Theorems in the Propositional Calculus %J Dokl. Akad. Nauk UzSSR %D 1986 %N 5 %P 5-6 %K AI11 %A Daniel N. Osherson %A Michael Stob %A Scott Weinstein %T Aggregating Inductive Expertise %J Inform. and Control %V 70 %D 1986 %N 1 %P 69-95 %K AI04 %A A. A. Voronkov %A A. I. Degtyarev %T Automatic Theorem Proving I. %J Kibernetika (Kiev) %V 1986 %N 3 %P 27-33 %A A. A. Lorents %T Cluster Invariant Transformations of Images %B Methods and Means of Transforming Information %E G. G. Gromov %N 3 %P 39-75 %I "Zinatne" %C Riga %D 1985 %A P. T. Cox %A T. Pietrzykowski %T Incorporating Equality into Logic Programming via Surface Deduction %J Ann. Pure Appl. Logic %V 31 %D 1986 %N 2-3 %P 177-189 %K AI10 AI11 %A Judith V. Grabiner %T Computers and the Nature of Man: A Historian's Perspective on Controversies About Artificial Intelligence %J Bull. Amer. Math. Soc. (n. S.) %V 15 %D 1986 %N 2 %P 113-126 %K AA11 AA25 AT20 AI16 %A Rolf Wiehagen %T On the Complexity of Program Synthesis from Examples %J Elektron. Informationsverarb. Kybernet %V 22 %D 1986 %N 5-6 %P 305-323 %K AA08 AI04 %A Kunihiko Kaneko %T Complexity in Basin Structures and Information Processing by the Transition Among Attractors %B Dynamical Systems and Nonlinear Oscillations (Kyoto 1985) %P 194-209 %S World Sci. Adv. Ser. Dyn. Syst. %I Word Sci. Publishing %C Singapore %D 1986 %K AI08 %A G. S. Pospelov %A D. A. Pospelov %A V. F. Khoroshevskyi %T International Basic Laboratory on Artificial Intelligence %J Vestnik Akademii Nauk SSSR %N 8 %D 1986 %P 76 %K AT19 %A R. G. Palmer %T How Expert Systems Can Improve Crop Production %J Agricultural Engineering %V 67 %N 6 %D SEP-OCT 1986 %P 28-35 %K AA05 AA23 AI01 %A G. Papakonstantinou %A C. Moraitis %A T. Panayiotopoulos %T An Attribute Grammar Interpreter as a Knowledge Engineering Tool %J Angewandte Informatik %N 9 %D SEP 1986 %K AI16 %A L. I. Lipkin %T Correct Models in Problems of Recognition with Random Information %J Dokl. Akad. Nauk SSSR %V 289 %D 1986 %N 4 %P 793-795 %K AI06 %X (in Russian) %A Maria Viorica Stefanescu %T The Problem of Best Approximation in the Theory of Hierarchical Classificatio n %J Stud. Cerc. Mat %V 38 %D 1986 %N 4 %P 392-408 %K O06 %X in Romanian with an English summary %A Xu Ding Zhu %A Xue Mou Wu %T Transformation of Pansystems Relations, Pansystems Clustering and Pansystems Recognition %J J. Huazhong Univ. Sci. Tech. %V 13 %D 1985 %N 6 %P 71-74 %X in Chinese with English summary %A S. S. Goncharov %A D. I. Sviridenko %T Mathematical Foundations of Semantic Programming %J Dokl. Akad. Nauk SSSR %V 289 %D 1986 %N 6 %P 1324-1328 %K AI10 AI11 AI16 %X in Russian %A Yoshihito Toyama %T On Equivalence Transformations for Term Rewriting %J RIMS Symposia on Software Science and Engineering II (Kyoto 183/184) %P 44-61 %S Lecture Notes in Computer Science %V 220 %I Springer-Verlag %C Berlin-New York %D 1986 %K AI10 %A Sergiu Hart %A Micha Sharir %T Probabilistic Propositional Temporal Logics %J Inform. and Control %V 70 %D 1986 %N 2-3 %P 97 %K AI10 %A Dell, Gary S. %T A Spreading-Activation Theory of Retrieval in Sentence Production %J Psychological Review %V 93 %N 3 %D 1983 %P 283-321 %K AI12 AI02 %A Fahlman, Scott E. %T Representing Implicit Knowledge %B Parallel Models of Associative Memory %E E Geoffrey E. Hinton %E James A. Anderson %D 1981 %I Lawrence Erlbaum Associates %C Hillsdale, New Jersey %K AI12 AI08 %A Fanty, Mark %T Context-Free Parsing in Connectionist Networks %R Tech Report TR174 %I Department of Computer Science, University of Rochester %D Nov. 1985 %K AI12 AI02 %A Feldman, Jerome A. %T A Connectionist Model of Visual Memory %B Parallel Models of Associative Memory %E Geoffrey E. Hinton %E James A. Anderson %D 1981 %I Lawrence Erlbaum Associates %C Hillsdale, New Jersey %K AT15 AI12 %A Feldman, Jerome A. %A Dana H. Ballard %T Connectionist Models and Their Properties %J Cognitive Science %V 6 %P 205-254 %D 1982 %K AI08 AI12 %A Feldman, Jerome A. %T Dynamic Connections in Neural Networks %J Biological Cybernetics %I Springer-Verlag %V 46 %D 1982 %P 27-39 %K AI08 AI12 %A Fodor, Jerry A. %T Information and Association %O This paper is a critique of connectionism. Author is with department of Philosophy, MIT, Cambridge Massachussetts. %K AI08 AI12 %A Hopfield, John J. %T Neural Networks and physical systems with emergent collective computational abilities %J Proceedings National Academy of Science %V 79 %P 2554-2558 %D Apr. 1982 %K AI08 AI12 %A Hopfield, John J. %A David W. Tank %T Simple "Neural" Optimization Networks: An A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit %J IEEE Transactions on Circuits and Systems %V CAS-33 %N 5 %P 533-541 %D May 1986 %K AI12 AA04 %A Hopfield, John J. %A David W. Tank %T Collective Computation with Continuous Variables %B Disordered Systems and Biological Organization %I Springer-Verlag %O In press, 1986 %K AI12 %A Hopfield, John J. %A David W. Tank %T "Neural" Computation of Decisions in Optimization Problems %J Biological Cybernetics %I Springer-Verlag %V 52 %D 1985 %P 141-152 %K AI12 %A Kosslyn, Stephen M. %A Gary Hatfield %T Representation without Symbol Systems %J Social Research %V 51 %N 4 %D 1984 %P 1019-1044 %O Winter 1984 %K AI12 %A Matthews, Robert J. %T Problems with Representationalism %J Social Research %V 51 %N 4 %D Winter 1984 %P 1065-1097 %K AI12 %A McClelland, James L. %A Jerome Feldman %A Beth Adelson %A Gordon Bower %A Drew McDermott %T Connectionist Models and Cognitive Science: Goals, Directions and Implications %D Jan. 1987 %O National Science Foundation Grant Proposal %K AI12 %A Plaut, David C. %J Visual Recognition of Simple Objects by a Connection Network %R Tech Report TR143 %I Computer Science Department, University of Rochester %D Aug. 1984 %K AI12 AI06 %A Pylyshyn, Zenon W. %T Computation and Cognition: Toward a Foundation for Cognitive Science %I MIT Press %D 1984 %C Cambridge, Massachusetts %K AI12 AI08 %A Reiss, Richard F. %T An Abstract Machine Based on Classical Association Psychology %B Proceedings 1962 Joint Computer Conference %I AFIPS %D 1962 %V 21 %K AI12 AI08 %A Shastri, Lokendra %A Jerome A. Feldman %T Semantic Networks and Neural Nets %R Tech Report TR131 %I Computer Science Department, University of Rochester %D June 1984 %K AI12 %A Schwartz, Robert %T "The" Problems of Representation %J Social Research %V 51 %N 4 %D 1984 %P 1047-1064 %O Winter 1984 %K AI12 %A Touretzky, David S. %A Geoffrey E. Hinton %T Symbols Among the Neurons: Details of a Connectionist Inference Architecture %J IJCAI %D Aug. 1985 %K AI12 %T Mathematical Methods in Software Science and Technology %I Kyoto University, Research Institute for Mathematical Sciences, Kyoto %C Kyoto %K AT15 %X Proceedings of a symposium held at the Research Institute for Mathematical Sciences, Kyoto University, Kyoto, October 4-6 1985 %A Cecylia M. Rauszer %T Remarks on Logic for Dependencies %J Bull. Polish Acad. Sci. Math %V 34 %D 1986 %N 3-4 %P 249-252 %A A. Aiello %A E. Burattini %A A. Massarotti %A F. Ventriglia %T Heuristic Evaluation Techniques for Bin Packing Approximation Algorithms %J Calcolo %V 22 %D 1985 %P 319-334 %A Ernest G. Manes %A Michael A. Arbib %T Algebraic Approaches to Program Semantics %S AKM Series in Theoretical Computer Science %I Springer-Verlag %C New York-Berlin %D 1986 %K AA08 AT15 %X ISBN 0-387-96324-3 351 pages %A Kazunori Ueda %T On the Operational Semantics of Guarded Horn Clauses %B Mathematical Methods in Software Science and Technology %C Kyoto %P 263-283 %D 1985 %K AI10 %X (in Japanese) %A A. I. Kondratev %T Game Theoretic Models in Problems of Recognition %I "Nauka" %C Moscow %D 1986 %K AT15 AI06 AI16 %X In Russian %A Etienne Paul %T On Solving the Equality Problem in Theories Defined by Horn Clauses %J Theoret. Comput. Science %V 44 %D 1986 %N 2 %P 127-153 %A Zbigniew Ras %A Maria Zemankova %T Learning in Knowledge Based Systems, A Possibilistic Approach %J Bull. Polish Acad. Sci. Math %V 34 %D 1986 %N 3-4 %P 235-247 %K AI04 O04 %A Takashi Yokomori %T Representation Theorems and Primitive Predicates for Logic Programs %B Mathematical Methods in Software Science and Technology %C Kyoto %D 1986 %P 1-17 %K AI10 %A Eric Degreef %A Jean-Paul Doignon %A Andre Ducamp %A Jean-Claude Falmagne %T Languages for the Assesment of Knowledge %J J. Math. Psychology %V 30 %D 1986 %N 3 %P 243-256 %K AA10 AI16 %A E. Diday %T A Visual Representation of Overlapping Clusters: Pyramids %J RAIRO Automat. Prod. Inform. Ind %V 20 %D 1986 %N 5 %P 475-526 %K O06 %A Michael Leyton %T A Theory of Information Structure. II. A Theory of Perceptual Organization %J J. Math Psychol. %V 30 %D 1986 %N 3 %P 257-305 %K AA10 AI08 AI16 %A Eliezer L. Lozinski %T A Problem Oriented Inferential Database System %J ACM Trans. Database Systems %V 11 %D 1986 %N 3 %P 323-356 %K AA09 %A R. P. Bergstrom %T AI - Shifting into High Gear %J Manufacturing Engineering %V 98 %N 1 %D JAN 1987 %K AI16 AT08 %A Gail A. Carpenter %A Stephen Grossberg %T A Massively Parallel Architecture for a Self-Organizing Neural Pattern Recognition Machine %J Computer Vision, Graphics, and Image Processing %V 37 %N 1 %D JAN 1987 %P 54-115 %K AT12 AI06 H03 %A Stephen Grossberg %A Ennio Mingollao %T Neural Dynamics of Surface Perception: Boundary Webs, Illuminants and Shape from Shading %J Computer Vision, Graphics and Image Processing %V 37 %N 1 %D JAN 1987 %P 116 %K AT12 AI06 AA10 %A Salvatore J. Stolfo %A Daniel P. Miranker %T DADO: A Tree-Structured Architecture for Artificial Intelligence Computation %B BOOK62 %P 1-18 %K H03 %A C. Raymond Perrault %A Barbara J. Grosz %T Natural-Language Interfaces %B BOOK62 %P 47-82 %K AI02 AA15 AT08 %A Hector J. Levesque %T Knowledge Representation and Reasoning %B BOOK62 %P 255-288 %K AI16 AT08 %A V. B. Robinson %A A. U. Frank %A M. A. Blaze %T Expert Systems Applied to Problems in Geographic Information Systems - Introduction, Review and Prospects %J Computers, Environment and Urban Systems %V 11 %N 4 %D 1986 %P 161-174 %A Michael W. Parks %T Artificial Intelligence, Part 2: Expert Systems Fill in the Missing Link %J Industrial Engineering %V 19 %N 1 %D JAN 1987 %P 36-47 %K AT08 AI16 %A M. B. Gorzalczany %T A Method For Inference in Approximate Reasoning Based on Interval Valued Fuzzy Sets %J Fuzzy Sets and Systems %V 21 %N 1 %D JAN 1987 %P 1-18 %K O04 %A N. Y. Salmina %A I. A. Khodashinskii %T Methods and Means of Automatic Correction of Spelling Errors %J Nauchno-tekhnicheskaya Informatsiya Seriya II - Informatsionnye Protessy I Sistemy %N 10 %D 1986 %P 25-28 %K AA15 %A J. Bartholdi, III %A M. A. Trick %T Stable Matching with Preferences Derived from a Psychological Model %J Operations Research Letters %V 5 %N 4 %D OCT 1986 %P 165-170 %K O04 AA11 %A K. K. Paliwal %A V. Ramsubramanian %T Vector Quantization in Speec Coding: A Review %J Indian Journal of Technology %V 24 %N 10 %D OCT 1986 %P 613-621 %K AI05 %A P. Leith %T Fundamental Errors in Legal Logic Programming %J The Computer Journal %V 29 %N 6 %D DEC 1986 %P 545-552 %K AA24 AI10 %A R. A. Frost %T Improving Output from Research (in the Domain of Knowledge Base Systems) %J The Computer Journal %V 29 %N 6 %P 572 %K AI01 AT19 %A P. Hajek %T A Simple Dynamic Logic %J Theoretical Computer Science %V 46 %N 2-3 %D 1986 %P 239-260 %K AI10 %A C. H. Huang %A C. Lengauer %T The Automated Proof of a Trace Transformation for a Bitonic Sort %J Theoretical Computer Science %V 46 %N 2-3 %D 1986 %P 261-284 %K AI11 AA08 %A A. Dicky %T An Algebraic and Algorithmic Method for Analysing Transition Systems %J Theoretical Computer Science %V 46 %N 2-3 %D 1986 %P 285-304 %A T. Hardinne %A A. Levinne %T Proof of Termination of the Rewriting System SUBST on CCL (Note) %J Theoretical Computer Science %V 46 %N 2-3 %D 1986 %P 305-312 %A Anton Bigelmaier %T Profile of a Geometrical Knowledge Base for CAD Systems %J Computers and Graphics %V 10 %N 4 %D 1986 %P 297-306 %K AA05 %A Taha I. Elareef %T Flavor System and Message Passing as Representation of Knowledge for Solid Modeling in CAD Expert System %J Computers and Graphics %V 10 %N 4 %D 1986 %P 351-358 %K AA05 T01 AI01 %A J. Bajon %A M. Cattoen %A L. Llang %T Identification of Multicoloured Objects Using a Vision Module %B BOOK63 %P 21-30 %K AI06 %A H. A. Laird %A K. R. Gilmour %A D. McKeag %T A Vision for Strain Analysis %B BOOK63 %P 31-40 %K AI06 %A H. Vanbrussel %A H. Belien %T A High Resolution Tactile Sensor for Part Recognition %B BOOK63 %P 49-60 %K AA26 AI07 AI06 ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 7 12:00:38 1987 Date: Sat, 7 Mar 87 12:00:27 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #70 Status: R AIList Digest Saturday, 7 Mar 1987 Volume 5 : Issue 70 Today's Topics: Policy - Hardware Discussions, Query - Eliza, Doctor, Parry, Ractor, etc, Applications - Analysis of Unknown Data & AI in Network Protocols ---------------------------------------------------------------------- Date: Thu, 5 Mar 87 12:24 EST From: Phil Stanhope Subject: Policy - Hardware Discussions >Date: Wed, 25 Feb 87 10:41:16 -0800 >From: Amnon Meyers >Subject: Hardware vs. AI > > I disagree with the notion that hardware problems have 'nothing to do with > AI'. While discussions of LISP and PROLOG dialects are interesting, they > appear to me to have no more relevance to 'AI' than do hardware issues. > Likewise discussion of the operation and environment provided by LISP > machines and other workstations. Likewise philosophical discussions of > the mind. My point is that it is not useful to try to define AI too > narrowly. There is a theory and practice of AI, and AILIST seems to stress > the theory. It would be nice if the 'practice' were taken up somewhere > as well. > > I can certainly understand that the AILIST is already overburdened, and > that the moderator already does too much work (and a fine job as well). > THOSE should be the reasons for excluding hardware issues, not arbitration > about what is and is not relevant to AI. I concur but would also like to add something that my father, who has never worked in the fields of computer science or artificial intelligence said to me awhile ago. He thought that AI should stand for the "Avoidance of Ignorance," which implies a few things: (1) intelligent behaviour, or the emulation thereof, helps one to solve problems ... (2) learning from mistakes, i.e., not remaining ignorant or naive about problems and their solutions ... (3) being able to inform other people/machines/users of ones knowledge that they've gained through experience ... If doing the above means learning more about: (1) software engineering techniques, algorithms, and languages (2) current research and its applications (3) hardware that is currently available (4) last but not least, the philosophical and epistemological underpinnings of intelligence and behaviour, then these are all valid topics of discussion that, given space and interest, should be posted on this list. Philip Stanhope Palladian Software, Inc. Cambridge, MA. 02142 [Agreed, but it is that "given space and interest" that is the troublesome part. My own orientation is towards algorithms and techniques. Software (e.g., expert system shells) is also discussed in AIList since it is so closely tied to techniques. The coupling to hardware is much looser, and there are already several lists relating to workstations and particular hardware systems. It seems logical to break off hardware as a separate discussion topic so that only those who are interested need to scan (and pay for) the traffic. The same may be true of other topics currently carried by AIList, but there seems to be a shortage of moderators. Most of the lists that have spun off (e.g., NL-KR@Rochester, neuron%ti-csl.csnet@RELAY.CS.NET) seem to be doing just fine, and I'm sure the readers appreciate the increased ease of culling and saving the messages of interest to them. -- KIL] ------------------------------ Date: 4 Mar 87 10:54:19 GMT From: mcvax!ukc!its63b!dougie@seismo.css.gov (D Nisbet) Subject: Eliza, Doctor, Parry, Ractor, etc, ... I have heard about the various "chatty" programs which have been written to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never had the opportunity to play (play?!) use any of these programs. This kind of software interests me a lot and would like to know if any of them (or similar type) are freely available. There is a book, I believe, titled "The Policeman's Beard is Half-Constructed" which chronicles the 'works' of one of these programs (I can't remember which). Does anyone know of its availability/publisher/price, and if there are any other recommended books in this kind of area. Any info appreciated. I will summarise any e-mail to me if there is any interest. [ .. I *know* this article is already in misc.misc. before anyone flames me for bad netiquette. I've had trouble trying to post to the more relevant ones. DJN ] -- Dougie Nisbet University of Edinburgh | ...seismo!mcvax!ukc!its63b!dougie Medical Statistics Unit | dougie@uk.ac.ed.its63b Medical School Teviot Place Edinburgh Scotland ------------------------------ Date: 6 Mar 87 00:20:25 GMT From: sonia!cracraft@locus.ucla.edu (Stuart M. Cracraft) Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ... In article <310@its63b.ed.ac.uk> dougie@its63b.ed.ac.uk (D Nisbet) writes: > >I have heard about the various "chatty" programs which have been written >to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never >had the opportunity to play (play?!) use any of these programs. This kind >of software interests me a lot and would like to know if any of them >(or similar type) are freely available. > Ractor is one of the funniest programs I've ever seen. I ran it on a Macintosh over at the local software shop, and it had me in stitches for almost an hour. (The stiches were recently removed by GNU-EMACS's `doctor' mode.) Stuart ------------------------------ Date: 5 Mar 87 12:40:36 GMT From: dave@mimsy.umd.edu (Dave Stoffel) Subject: analysis of unknown data What systematic methods and techniques would you apply to the following problem? Determine the representation, organization, and content of a "file" containing up to 156MB. There are no assumptions. The methods and techniques applied must be automated (if not fully automatic) and applicable to an unlimited supply of "files". ------------------------------ Date: 6 Mar 87 17:18:42 GMT From: ihnp4!houxm!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT) Subject: Re: analysis of unknown data In article <5681@mimsy.UUCP>, dave@mimsy.UUCP (Dave Stoffel) writes: > > What systematic methods and techniques would you apply to the > following problem? > > Determine the representation, organization, and content of a > "file" containing up to 156MB. There are no assumptions. What systematic or unsystematic methods and techniques would you apply to the following (seemingly easier) problem? Determine the machine language of a computer with a 64K address space, 8K of RAM, and 48K of ROM containing an operating system and BASIC. There is user documentation but no system documentation. The operating system has undocumented capabilities for writing in RAM, reading any byte, and starting execution at any byte in the address space. Ignore secondary storage. M. B. Brilliant Marty AT&T-BL HO 3D-520 (201)-949-1858 Holmdel, NJ 07733 ihnp4!houdi!marty1 ------------------------------ Date: 6 Mar 87 16:40:49 GMT From: ihnp4!houxm!houdi!marty1@ucbvax.Berkeley.EDU (M.BRILLIANT) Subject: Re: analysis of unknown data In article <5681@mimsy.UUCP>, dave@mimsy.UUCP (Dave Stoffel) writes: > What systematic methods and techniques would you apply to the > following problem? > > Determine the representation, organization, and content of a > "file" containing up to 156MB. There are no assumptions.... I thought that would be impossible. Theoretically, I would think that if there are no assumptions there can be no reasoning. In fact, there are always tacit assumptions that even the author isn't aware of. If I'm wrong, please post to the net, as I imagine there are others as naive as I am. M. B. Brilliant Marty AT&T-BL HO 3D-520 (201)-949-1858 Holmdel, NJ 07733 ihnp4!houdi!marty1 ------------------------------ Date: 6 Mar 87 18:55:17 GMT From: Robert Stanley Subject: Re: AI in Network Protocols. In article <8702280810.AA09316@cs-gw.D.UMN.EDU> ramarao@umn-cs.UUCP.UUCP writes: > >topic : EXPERT SYSTEMS OR AI IN NETWORKS AND PROTOCOLS > > I am trying to find out if there has been any attempt at >applying AI techniques, AI languages to the field of network protocols. > There seems to be more than one question being asked here, and some fairly fundamental confusion about so-called AI languages. It is perfectly possible to create communications protocols of almost any kind using LISP or PROLOG (or less well-known object-oriented languages such as NEON) provided that there is a clean interface to the underlying system. The InterLisp-D world on the Xerox 1100 series machines is a good example. However, this has nothing to do with AI. Is it possible to apply AI techniques in creating protocols? Yes, of course, but most of the work that has come to my attention appears to have been tackling the problems of network configuration, diagnostics, and routing. Why would anyone want to to "use AI" to write a protocol? This is a hard-science engineering issue, and one that is pretty well nailed shut for existing protocols. The key to protocols has tended to be universal standardization, so that many people can use them. One area that it would be interesting to see AI applied is the smart "automatic" conversion between protocols. I suppose the last interptretation of the question is: could a new protocol be created which is based on AI techniques? Again, one supposes so, but such things have a habit of being created only when there is a clearly apparent need. I have not currently got any communications problems (telecommunications problems, anyway) that can't be solved by applying existing protocols, and I find that 10megabit LAN and 1.27megabit GAN are sufficiently wide bandwidths for all my current needs. Perhaps the original posting could be rephrased or expanded slightly, to open a possibly interesting topic for discussion. Robert Stanley -- Robert Stanley decvax!utzoo!dciem!nrcaer!cognos!roberts Voice: (613) 738-1440 (on EST) Tuesdays only don't ask-----' Cognos Inc., 3755 Riverside Drive, Ottawa, Ontario, K1G 3N3 CANADA ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 7 12:00:54 1987 Date: Sat, 7 Mar 87 12:00:42 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #71 Status: R AIList Digest Saturday, 7 Mar 1987 Volume 5 : Issue 71 Today's Topics: News - IJCAI Research Excellence Award, Expert Systems - Explanations, Philosphy - Consciousness ---------------------------------------------------------------------- Date: Fri, 6 Mar 87 09:35:16 GMT From: Alan Bundy Subject: Announcement: IJCAI Research Excellence Award THE 1987 IJCAI AWARD FOR RESEARCH EXCELLENCE I regret to announce that the IJCAI-87 Awards Committee, having considered all the candidates nominated for the Research Excellence Award, have decided not to make an award. The Award is given in recognition of an Artificial Intelligence scientist who has carried out a program of research of consistently high quality yielding several substantial results. The first recipient of this award was John McCarthy in 1985. In the opinion of the Awards Committee none of the nominated candidates reached the high standard required. Several members of the Committee afterwards suggested candidates that, in their opinion, did reach the required standard, but who had not been nominated. Nominations for the Award were invited from all in the artificial intelligence international community. The Award Committee was the union of the Programme, Conference and Advisory Committees of IJCAI-87 and the Board of Trustees of IJCAII, with nominees excluded. It is the sincere hope of all the Committee that, in future years, a greater effort will be made by the artificial intelligence community to nominate suitable candidates. Alan Bundy IJCAI-87 Conference Chairman ------------------------------ Date: Fri, 6 Mar 87 9:42:17 EST From: Bruce Nevin Subject: Re: dear Abby The bounds of a field are subject to redefinition. Many established fields of today were interdisciplinary in the past. Thus, `when not to step past them' is a complex matter. Is it possible for users of an expert system to ask for information outside its domain, and for it to answer naively, overstepping its proper bounds? Has anyone worked with this level of meta-expertise? For instance, are there systems that address multiple domains and select the appropriate one (or combination) by deduction from interactions with the user? Bruce Nevin bn@cch.bbn.com (This is my own personal communication, and in no way expresses or implies anything about the opinions of my employer, its clients, etc.) ------------------------------ Date: Thu, 05 Mar 87 08:13:33 EST From: sriram@ATHENA.MIT.EDU Subject: Expert Systems and Explanations Knowledge-based system technology is a programming methodology, which facilitates the incorporation of "human or expert" knowledge. Hence, the criterion that explanation facilitiy is a must for a knowledge based system (or an expert system once you add the expert's knowledge) is to be questioned. In fact, our experience with building expert systems indicates that the end user is least bothered about seeing things like: Rule XX concluded that YY is true. That stuff is good for debugging purposes. For the explanations to be accepted by end users a more robust ENGLISH translation should be provided (for example Swartout's work). Further, I feel the selling point for any expert system will be the USER INTERFACE (with nice graphics). Sriram ------------------------------ Date: 5 Mar 87 15:08:41 GMT From: ihnp4!ihuxv!arrgh@ucbvax.Berkeley.EDU (Hill) Subject: Explanations in expert systems I have to put in my $0.02 into the expert systems discussion. In real life, an expert system probably will not be used unless it possesses a sound explanation facility. For most users, this does not mean merely dumping rules or whatever, e.g., "the system is trying to satisfy rule-518", but rather being able to turn the knowledge encoded in each unit of representation into meaningful natural language. An example may make this requirement clearer. One of the systems I have built is the Michael Reese-IIT Stroke Consultant. This program is a large neurology expert system designed to assist house physicians with the diagnosis and treatment of stroke. One of the treatments this system recommends is to prep the patient for surgery, take him into the OR, remove the back of his head, and proceed to dig around in the cerebellum for a hematoma. Naturally enough, any reasonable physician will want to ask the machine "WHY?" it recommends such a radical treatment, and expect an answer in a form that a physician (not a computer scientist) can understand. The explanation system will furnish: an English statement of the problem, e.g., "diagnosis is hemorrhage into the cerebellum", and justifications for the treatment, e.g., "Evacuation of cerebellar hematoma is recommended because it greatly reduces mortality when the following signs are present... Refer to the following references [references to the neurology literature are cited]." Lets take a more common case. Last spring, I built an expert system that is designed to diagnose problems in candy wrapping machinery. In fact, if you eat candy bars, you have almost certainly eaten candy wrapped on one of these machines. The operators of these machines needed additional help in diagnosing and troubleshooting problems in this new equipment, and we built an expert system for this specific task. Machine operators, unlike many of you, have absolutely no understanding of production rules, and moreover, they are not interested. This system had to be able to furnish the following explanations on line at all times: (1) how to use system itself, (2) how the candy wrapping equipment was supposed to operate (an on line tutorial on the machine), (3) how to answer the questions the system was asking, e.g., where was IC 9 pin 7 on the Micro controller "A" board, and (4) an explanation of the reasoning the system was using at that time. The moral of this rather long posting is that if you want to build expert systems that will actually be used by real people you will need a good explanation facility. While this is necessary, it is of course, not sufficient. The knowledge engineer will need good debugging facilities (something not provided on most tools today). Hope this clears up some confusion. -- Howard Hill, Ph.D. ------------------------------ Date: 6 Mar 87 23:01:45 GMT From: cbatt!osu-eddie!tanner@ucbvax.Berkeley.EDU (Mike Tanner) Subject: Re: Explanations in expert systems In article <1800@ihuxv.ATT.COM> arrgh@ihuxv.ATT.COM (Hill) writes: > >In real life, an expert system probably will not be used unless it possesses >a sound explanation facility. For most users, this does not mean merely >dumping rules or whatever, e.g., "the system is trying to satisfy >rule-518", but >rather being able to turn the knowledge encoded in each unit of representation >into meaningful natural language. > While I agree that spitting out rules is generally inadequate for explanation I disagree that explanations *must* be in natural language. For some kinds of explanation drawing and pointing is more useful. "I think the wonkus is broken. Try replacing it." "Wonkus!? What's that?" "Take a look at the zweeble smasher. See this gizmo? That's the wonkus." I'm not saying natural language is useless. But the above interaction would have taken a lot more words without the picture. (With the picture it might have needed no words at all. But I don't know what a zweeble smasher is, much less how to draw one.) Sometimes a picture really is worth a thousand words. Keep in mind that when you talk about explanation as giving back rules you're assuming expert systems are simple, flat rule-bases. This is not necessarily true. If all your expert system knows is rules then: (a) the system isn't doing anything interesting OR (b) you're actually using the rule language as a general purpose programming language (because rules qua rules don't give you the control features needed to navigate a large knowledge base) In case (a), there's no need to worry about real world usefulness. In case (b), there should be no surprise that the rules themselves are not informative explainers. No more than a listing of code would, in general, be an explanation of a program. -- mike ARPA: tanner@ohio-state.arpa UUCP: ...cbosgd!osu-eddie!tanner ------------------------------ Date: Thu, 5 Mar 87 09:24:51 pst From: Eugene Miya N. Subject: Consciousness Do not confuse consciousness with memory. Consciousness is not a dualistic phenomena which your "speculation" (your word) tends to imply. Consider that you did not mentioned subconscious (explicitly), and but you did mention a dual unconscious. Your comments on memory can also be refined by the cognitive literature such as the distinction between recall, recognition, and the two other types of memory tests I am forgetting. You also should make a distinction between forgetting and interference (this is good). My suggestion is for you to visit a nearby college or university and get some literature on cognition (of which I am NOT a proponent). >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?" "Send mail, avoid follow-ups. If enough, I'll summarize." {hplabs,hao,ihnp4,decwrl,allegra,tektronix,menlo70}!ames!aurora!eugene ------------------------------ Date: Fri, 06 Mar 87 12:01:36 n From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu Subject: philosphy - consciousness Could an unconscious machine be a good psychologist ? ***************************************************** During the recent discussions on consciousness, Stevan Harnad has, in the face of many claims about its role/origin, given us the demanding question "well, if X is achieved *with* consciousness, why couldn't it be accomplished *without* ?" (I hope I have understood this much correctly). I think that many of those arguing with Harnad, myself included, have not appreciated the full implications of this question - I wish now to give one example of "an X" designed to at least point in the direction of an answer to Harnad's question. I hope that Stevan would accept, as a relatively axiomatic truth, that for complex systems (eg; ourselves, future compsys'), interaction and 'social development' are a *good thing*. That is to say, a system will do better if it can interact with others (particularly of its kind), and even more so if such interactions are capable of development towards structures resembling 'societies'. We can justify this simply on the grounds of efficiency, information exchange, and altruistically-based mutual survival arrangements (helping each other out). I think that this is as true of computer systems as human beings, although its curent implementation lacks any real capacity for self-development. Given this axiom - that complex systems will do better if they interact - we may return to the hypothesis of Armstrong, recently raised by M.Brilliant on the ailist, that the selective advantage conferred by being conscious is connected with the ability to form developing social systems. Harnad's question in this context (previously raised) is "why couldn't an unconscious TTT-indistinguishable automaton accomplish the same thing ?". So, lets look at this proposition. In order to accomplish meaningful social interactions in a way that opens up such relations to future development it is necessary to be able to predict - not, of course with 100% accuracy, but to an extent that permits mutual acts to occur without running through all the verbal preliminaries every time (conceptually similar to installing preamble macros in TeX - a facetious statement!). Our ability to do this is described in every day experience as 'understanding other people', and permits us to avoid asking the boss for a raise when he is obviously in a foul mood. Rephrasing Harnad's question in an even more specific (and revealing) manner, we now have " why couldn't an unconscious TTT-indistinguishable automaton make similarly good predictions about other conscious objects ?". We now have a useful fusion of biological, psychological and computer terms. What sort of computer systems do we know of that are able to make predictions? Although the exact definition is currently under debate ( see the list ),it seems that we may subsume such systems under the general term "expert systems"- used here in the most general sense of being an electronic device with access to a knowledge base and some method of drawing conclusions given this knowledge and a specific query or situation. I hope that Stevan will go along with this as a possible description of his TTT-indistinguishable automaton. So, could such a system 'understand' other people ? I believe that it could not, for the following reasons. As sophisticated as this 'inference engine' may be, its methods of reasoning must still, even in some high level sense, be instantiated by its designers. Moreover, its knowledge base is expandable only by observation of the world. To behave in a way that was TTT-indistinguishable from a human in its capacity to 'understand' people, this automaton would either (1) have to have a built in model of human psychology or (2) be capable of collecting information that enabled it to form its own model over time. Here we have reached the kernel of the problem. Do we have, or are we ever likely to have our own model of human psychology that is capable of being implented on a computer ? Obviously, this is open to debate, but I think not. The human approach to psychology seems to me to be incapable of developing in a context which does not take the participation and prior knowledge of the psychologist into consideration. As sophisticated as it gets, I feel (though you're welcome to try and change my mind) that psychology will always be like a dictionary - you look up the meaning of one word, and find you have to know 30 others to understand what it means. Alternatively, suppose that our fabulous machine were to try and 'figure it out fo itself'. It will very soon run into a problem. When it asks someone why they did something, it will recieve a reply which often involves a reference to an 'inner self' - a world, which as any good psychologist will tell you, has its own rules, its own objects and its own interactions. The machine asks, and asks, observes and observes - will it ever be able to put together a picture of the 'inner life' of these conscious humans ? And now we are at the end. Its obviously a statement of faith, but I believe that what consciousness gives us is the ability to do just what this machine cannot - to be a good psychologist. It makes this possible by allowing us to *compare and contrast* our own behavior and 'inner self' with other's behaviour - and hence to make the leap of understanding that gives rise to the possibility of meaningful social interaction and development. We have our *own* picture of 'inner life' (this is not meant to be mystical!) and hence we have no need to seek to develop a model by inference. I do not believe (now!) that an unconscious device could do the latter, and hence I do not think that it is possible, even in principle, to build an unconscious TTT-indistinguishable automaton that is capable of interacting with conscious objects. Thankyou, and good night. Paul Davis wetmail: embl, postfach 10.2209, 6900 heidelberg, west germany netmail: davis@embl.bitnet petmail: homing pigeons to ....... ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Tue Mar 10 00:48:10 1987 Date: Tue, 10 Mar 87 00:48:04 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #72 Status: R AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 72 Today's Topics: Seminars - TI AI Satellite Symposium & Ping Pong Playing Robot (UPenn) & Using Uncertainty to Solve Analogies (SMU) & AI and Expert Systems PDS (Los Angeles ACM) & Updating Databases with Incomplete Information (UPenn) & Filter Model of Types for Flexible Programming (UPenn) ---------------------------------------------------------------------- Date: 4 Mar 87 17:06:57 EST From: Peter.Capell@gnome.cs.cmu.edu Subject: Seminar - TI AI Satellite Symposium IEEE sponsors... The TEXAS INSTRUMENT'S Third Artificial Intelligence Satellite Symposium Wednesday, April 8, 1987 8:30 AM - 3:30 PM Presenters: Dr. Edward A. Feigenbaum - AI pioneer, author and lecturer, Stanford University educator and past president of the American Association of Artificial Intelligence. Dr. George Heilmeier - Senior Vice President and Chief Technical Officer of Texas Instruments, former Director of the Defense Advanced Research Projects Agency (DARPA). Dr. Alan C. Kay - Apple fellow, pioneer and key innovator in personal computing and artificial intelligence. Invented "Smalltalk" computer language and pioneered the use of icons. Dr. Douglas B. Lenat - Principal Scientist for Microelectronics and Computer Technology Corporation (MCC), pioner in machine learning through study of the nature of heuristics. Dr. Roger C. Schank - Professor of Computer Science and Psychology, Yale University, and Chairman of Cognitive Systems, Inc. Pioneer in development of computer models of memory and learning. Dr. Herbert Schorr - Group Director of Products and Technology, IBM. Responsible for the introduction of new advanced technology and applications. Dr. Harry R. Tennant - roundtable host, Senior Member Technical Staff and Manager of AI Research in Texas Instruments Computer Science Laboratory. Inventor of the concept of menu-based natural language understanding. Abstract: (see February IEEE Spectrum for more details) In four hours, Symposium III will examine the very latest developments, applications and future potential - from diverse perspectives. It will broaden the view of AI beyond knowledge-based systems to include natural language processing and rapid prototyping of both AI and conventional software. Site (for CMU): The APICS "castle" in Wilmerding Directions: Lee Ann Goettel: 825-3000 Fee: $6.00 (to cover doughnuts and lunch, Texas Instruments isn't charging anything for the downlink) Checks payable to: "APICS" or cash accepted Registration and information: Call or write - Attn: Peter Capell (Education Chair) Center for Art and Technology 111 CFA Carnegie Mellon University Pittsburgh, PA 15213 X-8862 ------------------------------ Date: Thu, 5 Mar 87 13:02:22 EST From: tim@linc.cis.upenn.edu (Tim Finin) Subject: Seminar - Ping Pong Playing Robot (UPenn) Dissertation Defense Computer and Information Science University of Pennsylvania Real Time Expert System to Control a Robot Ping Pong Player R.L. Andersson A real time "expert" control system has been designed and forms the nucleus of a functioning robot ping pong player. Robot ping pong is underconstrained in the task specification (hit the ball back), and heavily constrained by the manipulator capabilities. The expert system must integrate the sensor data, robot capabilities, and task constraints to generate an acceptable plan of action. The robot ping pong task demands that the planner anticipate environmental changes occurring during planning and robot motion. The inability to generate accurate, timely plans even in the face of a capricious environment and limited actuator performance would result in a nonfunctional system. The program must continuously update the task plan as new sensor data arrives, selecting appropriate modifications to the existing plan, rather than treating each datum independently. The difficult task and the stream of sensor data result in an interesting system architecture. The expert system operates in the symbolic and numeric domains, with a blackboard to enable global optimization by local agents. The architecture interrelates initial planning, temporal updating, and exception handling for robustness. A sensor and processing system produces three dimensional position, velocity, and spin vectors plus a time coordinate at 60 Hz. Novel processing algorithms and careful attention to camera modeling were necessary to obtain adequate accuracy. A robot controller provides accurate, predictable performance close to the envelope of robot capabilities using modeling and feed-forward techniques. The controller allows motions to be planned in the temporal domain including specified terminal velocities, and supports smooth changes to motions in progress. Performance of the sensor subsystem, actuator and robot controller, and expert system will be demonstrated. The system successfully plays against both human and machine opponents. COMMITTEE: DR. LOU PAUL (ADVISOR) DR. TIM FININ DR. RUZENA BAJCSY DR. ROD BROOKS (MIT) DATE: MARCH 27, 1987 TIME: 10-12 NOON LOCATION: 129 MOORE (FACULTY LOUNGE) ------------------------------ Date: Thu, 5 Mar 1987 17:34 CST From: Leff (Southern Methodist University) Subject: Seminar - Using Uncertainty to Solve Analogies (SMU) Seminar Announcement, Southern Methodist University, Department of Computer Science, Wednesday, Mar 11, 1987, 315 SIC, 1:30PM USING UNCERTAINTY TO SOLVE ANALOGIES David Rogers Cognitive Science and Machine Intelligence Laboratory University of Michigan Abstract Analogy involves the conceptual mapping of one situation onto another, assigning correspondences between objects in each situation. Uncertainty concerning the values of the objects' attributes or the correct category of an object is commonly considered a nuisance of little theoretical importance. In contrast, in this approach uncertainty is central: all attributes are to some degree uncertain, and category assignment of objects is fluid. Thanks to this all-pervading uncertainty (rather than dispite it), this architecture allows the system to represent the multiple, often conflicting pressures that guide our perceptions of situations in an analogy. Further, parallelism without global control is intrinsic in this architecture. Control is distributed throughout the system, at the level of its most primitive objects -- entities -- each entity communicating with a small number of other entities in the world. I will present a domain that uses deceptively simple strings of letters, followed by a description of the architecture used to solve problems in this domain. Finally, some results from a program written to implement these ideas will be presented. ------------------------------ Date: 6 Mar 87 06:40:39 PST (Friday) From: Chapman.ESM8@Xerox.COM Subject: Seminar - AI and Expert Systems PDS (Los Angeles ACM) (I am not on this dl, so please direct any questions directly to me. Thanks.) LA ACM is sponsoring a Professional Development Seminar on Artificial Intelligence and Expert Systems Saturday 18 April 9am-5pm at the LAX Hilton, 5711 Century Blvd., Los Angeles. Registration begins at 8 am. Lunch and course notes are included. PROGRAM Richard Korf: Introduction to AI & Expert Systems Ron Citrenbaum: A Practical Approach to Expert System Development Michael Dyer: Language and Thought: Symbolic and Subsymbolic Bill Swartout: Making Expert Systems Explainable Pat Langley: Overview of Problems and Techniques of Machine Learning COST: before 31 March after 31 March ACM member $80 $100 non-ACM $100 $120 full-time students* $5 call Cheryl *(with proof of full-time student status. Lunch & notes not included; on a space-available basis only.) Attendance is limited to 150. TO REGISTER: send your name, company name, address, home and business phone numbers, and cheque payable to LA ACM to: Cheryl Chapman, Xerox Corp, 701 S. Aviation Blvd ESM8-003, El Segundo, CA 90245 (213)606-0639. (For statistics purposes, please mention this message.) ------------------------------ Date: Fri, 6 Mar 87 14:12:57 EST From: tim@linc.cis.upenn.edu (Tim Finin) Subject: Seminar - Updating Databases with Incomplete Information (UPenn) COLLOQUIUM Computer and Information Science University of Pennsylvania UPDATING DATABASES WITH INCOMPLETE INFORMATION Marianne Winslett Stanford University Computer Science Department Suppose one wishes to construct, use, and maintain a database of facts about the real world, even though the state of that world is only partially known. In the artificial intelligence domain, this problem arises when an agent has a base set of beliefs that reflect partial knowledge about the world, and then tries to incorporate new, possibly contradictory knowledge into this set of beliefs. In the database domain, one facet of this situation is the well-known null values problem. We choose to represent such a database as a logical theory, and view the models of the theory as representing possible states of the world that are consistent with all known information. How can new information be incorporated into the database? For example, given the new information that ``b or c is true,'' how can one get rid of all outdated information about b and c, add the new information, and yet in the process not disturb any other information in the database? In current-day database management systems, the difficult and tedious burden of determining exactly what to add and remove from the database is placed on the user. The goal of our research was to relieve users of that burden, by equipping the database management system with update algorithms that can automatically determine what to add and remove from the database. Under our approach, new information about the state of the world is input to the database management system as a well-formed formula that the state of the world is now known to satisfy. We have constructed database update algorithms to interpret this update formula and incorporate the new information represented by the formula into the database without further assistance from the user. In this talk we will show how to embed the incomplete database and the incoming information in the language of mathematical logic, explain the semantics of our update operators, and discuss the algorithms that implement these operators. March 9, 1987 Room 216 Moore 3:00 to 4:30 Refreshments Available 2:30 to 3:00 ------------------------------ Date: Fri, 6 Mar 87 17:00:25 EST From: dale@linc.cis.upenn.edu (Dale Miller) Subject: Seminar - Filter Model of Types for Flexible Programming (UPenn) Math/CS Logic Seminar Filter Model of Types for Flexible Programming Atsushi Ohori (ohori@cis.upenn.edu) CIS Dept, Univ of Penn 16 March 1987 In this talk, I will present a mathematical model of data types for flexible programming. This model can give precise semantics to (1) polymorphic types, (2) type inheritance used in object-oriented programming, (3) parametric types, (4) dependent types, (5) recursive types and (6) higher-order types. I will also discuss some connections to ``formulae-as-types'' principle. We consider types as properties of values and define the semantics of types as the sets of values having those properties. This idea leads us to define types as principal filters in the underlying value domain (in the sense of Scott.) Since principal filters are represented by their minimal elements, types are represented by values. Simple type constructors are then correspond to operations on the value domain. The polymorphic type constructor corresponds to the least upper bound operation. Parametric types and dependent types are represented by functions on the value domain. Since the set of all principal filters is isomorphic to the underlying value domain, the semantic space of types is isomorphic to the value domain. This property allows us to give semantics to arbitrarily higher-order types without any inconsistencies. [Talk will be in Math Seminar Room, 4th floor DRL.] ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Tue Mar 10 00:48:24 1987 Date: Tue, 10 Mar 87 00:48:14 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #73 Status: R AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 73 Today's Topics: Administrivia - AI Hardware & Related Lists, Games - Computer Chess Article in March 6 New Yorker, Conferences - Volunteers for AAAI-87 & ACL Europe Copenhagen Conference & European Conference on Object-Oriented Programming 1987 ---------------------------------------------------------------------- Date: Sat, 7 Mar 87 13:12:24 est From: Arun Welch Subject: Re: Policy - AI Hardware About 6 months ago, I offered to moderate a list for discussing AI hardware, and asked that people who would be interested in such a list send me their names and email addresses. I got all of 5 responses. It didn't seem to me to be worth starting up a list for that small an audience... The offer still stands, I guess, though I doubt if I'm going to get more response.... ...arun ---------------------------------------------------------------------------- Arun Welch Lab for AI Research, Ohio State University {ihnp4,cbosgd}!osu-eddie!welch welch@ohio-state.{CSNET,ARPA} welch@red.rutgers.edu (a guest account, but mail gets to me eventually) ------------------------------ Date: Sun 8 Mar 87 20:56:40-PST From: Ken Laws Reply-to: AIList-Request@SRI-AI.ARPA Subject: Related Lists John Snyder has asked that I publish a list of AI-related discussion lists. The following is taken from the welcome message that I send to new AIList subscribers. I don't have a corresponding list of Usenet interest groups. Logic programming, theorem proving PROLOG@SUSHI.STANFORD.EDU AI in education, user modeling AI-ED@SUMEX-AIM Natural language, representation NL-KR@ROCHESTER Information retrieval IRLIST%VPI.CSNET@CSNET-RELAY Philosophy METAPHILOSOPHERS%MIT-OZ@MC.LCS.MIT.EDU Psychology EPSYNET%UHUPVM1.BITNET@WISCVM Neural networks neuron%ti-csl.csnet@CSNET-RELAY Vision algorithms, perception VISION-LIST@ADS Color and vision research CVNET%YORKVM1@WISCVM.WISC.EDU Programming languages, interfaces SOFT-ENG@MIT-XX Common Lisp COMMON-LISP@SU-AI Common Lisp windows CL-WINDOWS@SAIL.STANFORD.EDU X windows XPERT@ATHENA.MIT.EDU Scheme (a Lisp dialect) SCHEME@MC.LCS.MIT.EDU XLisp INFO-XLISP@SPICE.CS.CMU.EDU Workstations WORKS@RUTGERS Symbolics products SLUG@UTEXAS-20 Xerox Lisp machines, Interlisp INFO-1100@SUMEX-AIM BUG-1100@SUMEX-AIM Texas Instruments workstations INFO-TI-EXPLORER@SUMEX-AIM BUG-TI-EXPLORER@SUMEX-AIM Parallel symbolic computing PARSYM@SUMEX-AIM Symbolic math NET.MATH.SYMBOLIC (USENET) Arpanet list policy LLP@MC.LCS.MIT.EDU The list moderator can usually be reached by appending -REQUEST to the list name. For a full list of lists and their moderators contact Zellich@SRI-NIC. -- Ken Laws ------------------------------ Date: 07-Mar-1987 1749 From: minow%thundr.DEC@decwrl.DEC.COM (Martin Minow THUNDR::MINOW ML3-5/U26 223-9922) Subject: Computer Chess article in March 6 New Yorkr An interesting article in the current (on newstands till next Tuesday or so) New Yorker on the Fifth World Computer Chess Championship interviews many of the participants (Hans Berliner and Ken Thompson, for example) and touches on many of the "intelligence" and "conscious" issues. The article was written by Brad Leithauser. Martin Minow minow%thundr.dec@decwrl.dec.com ------------------------------ Date: Sat, 7 Mar 87 12:32:13 PST From: feifer@CS.UCLA.EDU Reply-to: feifer@CS.UCLA.EDU (Richard Feifer) Subject: Conference - Volunteers for AAAI-87 ANNOUNCEMENT: Student Volunteers Needed for Artificial Intelligence Conference AAAI-87 AAAI-87 (American Association on Artificial Intelligence) will be held July 13-17, 1987 in beautiful Seattle, Washington. Student volunteers are needed to help with local arrangements and staffing of the conference. To be eligible for a Volunteer position, an individual must be an undergraduate or graduate student in any field at any college or university. This is an excellent opportunity for students to participate in the conference. Volunteers receive FREE registration at AAAI-87, conference proceedings, "STAFF" T-shirt, and are invited to the volunteer party. More importantly, by participating as a volunteer, you become more involved and meet students and researchers with similar interests. Volunteer responsibilities are varied, including conference preparation, registration, staffing of sessions and tutorials and organizational tasks. Each volunteer will be assigned twelve (12) hours. If you are interested in participating in AAAI-87 as a Student Volunteer, apply by sending the following information: Name Electronic Mail Address USMail Address Telephone Number(s) Dates Available Student Affiliation Advisor's Name to: feifer@locus.ucla.edu or Richard Feifer UCLA Center for the Study of Evaluation 145 Moore Hall Los Angeles, California 90024 Thanks, and I hope you join us this year! Richard Feifer Student Volunteer Coordinator AAAI-87 Staff ------------------------------ Date: Sun, 8 Mar 87 18:04:03 est From: walker@flash.bellcore.com (Don Walker) Subject: Conference - ACL Europe Copenhagen Conference, 1-3 April 1987 ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: EUROPEAN CHAPTER Third Conference and General Meeting April 1-3 1987, University of Copenhagen Due to communication problems, the first registration circular announcing the Conference did not get sent to most ACL members. The attached information contains the programme, which was just released, together with information on registration (which because of the short time must now be down at the meeting) and hotels. For further information, contact: Bente Maegaard (ACL) IAML Njalsgade 96 DK-2300 Kobenhavn S, DENMARK 45-1-542 211, x2478 Bente_Maegaard_eurotra-dk%eurokom@mit-multics.arpa The conference will be held at the University of Copenhagen (Amager), Njalsgade 80, DK-2300 Copenhagen S, DENMARK, which is about 10 minutes by bus from the center of the city. REGISTRATION will take place on March 31 from 17 p.m. to 21 p.m., at the Institute of Applied and Mathematical Linguistics (Institut for Anvendt og Matematisk Lingvistik=IAML), University of Copenhagen/Amager, room 6.3.65 (stairway 6, third floor, room 65). The registration room will be easily found if you enter the university by the main entrance (Njalsgade 80) and follow the signs. It will also be possible to register on April 1st from 8.30 a.m. to 9.30 a.m. or, if necessary, during the conference. [... I'll let the NL-KR list carry the full provisional programme and hotel details. Or reply to the message author for a copy. -- KIL] ------------------------------ Date: Tue, 3 Mar 87 12:51 N From: DESMEDT%HNYKUN52.BITNET@wiscvm.wisc.edu Subject: Conference - ECOOP 1987 Here is an Advance Program for the European Conference on Object Oriented programming which was sent to me by Henry Lieberman (Henry@ai.ai.mit.edu): Advance Program ECOOP'87 June 15-17 Paris Palais des Congres Monday, June 15 2pm-3pm Invited Lecture Adele Goldberg (Xerox PARC & ParcPlace Systems) Session-1 METHODOLOGY Chairman: Luc Steels (Brussels University) 3:00-3:30 Delta Talk: An Empirical and Aesthetical Motivated Simplification of the Smalltalk-80 Language. Alan Borning (University of Washington) & Tim O'Shea (Xerox PARC) 3:30-4:00 Reversible Object-Oriented Interpreters Henry Lieberman (MIT) 4:30-5:00 Using Types and Inheritance in Object-Oriented Languages Daniel C. Halbert (DEC Hudson) & Patrick D. O'Brien (DEC Hudson) 5:00-5:30 Inheritance Mechanisms in Object-Oriented Concurrent Languages Jean-Pierre Briot (TIT,LITP) & Akinori Yonezawa (TIT) 5:50-6:00 On Including Part Hierarchies in Object-Oriented Languages, with an implementation in Smalltalk Edwin Blake (Queen Mary College) & Steve Cook (Queen Mary College) Tuesday, June 16 9:00-10:00 What is Object Oriented Programming? Bjarne Stroustrup (AT&T,Bell) Session-2: IMPLEMENTATION Chairman: J.F. Perrot (University of Paris 6) 10:00-10:30 Object Representation of Scope During Translation S. C. Dewhurst (AT&T) 11:00-11:30 Dynamic Grouping in an Object Oriented Virtual Memory Hierarchy Ifor Williams, Mario Wolczko & Trevor Hopkins (University of Manchester) 11:30-12:00 Traveler: The Apiary Observatory Carl Manning (MIT) 2:00-3:00 Strenghts and Weaknesses of Object Oriented Programming Paradigm Carl Hewitt (MIT) Session-3: THEORY Chairman: H. Stoyan (Konstanz University) 3:00-3:30 Classification of Actions or Inheritance also for methods Bent Krinstensen (University of Alborg), Ole Madsen (University of Alborg), Birger Moller-Pedersen (Norwegien Computing Center) & Kristen Nyggard (University of Oslo) 3:30-4:00 Semantics of Smalltalk-80 Mario Wolczko (University of Manchester) Session-4: INTERFACE Chairman: P. Greussay (University of Paris-8) 4:30-5:00 The Construction of User Interfaces and the Object Paradigm Joelle Coutaz (IMAG) 5:00-5:30 The ZOO Metasystem: A Direct-Manipulation Interface to Object-Oriented Knowledge Bases. Wolf Riekert (University of Stuttgart) 5:30-6:00 The Filter Browser. Defining Interfaces Graphically Raimund Ege (Oregon Graduate Center), David Maier (Oregon Graduate Center) and Alan Borning (University of Washington) Wednesday, June 17 Session-5: DISCUSSION-PAPERS (9:00-10:00) see end of this message Session-6: LANGUAGE IMPLEMENTATION Chairman: G. ATTARDI (DELPHI) 10:30-11:00 Concurrency Features for the Treillis/Owl Language J. Moss & W. Kohler (University of Massachusetts) 11:00-11:30 Objects as Communicating Prolog units Paola Mello & Antonio Natali (University of Bologna) 11:30-12:00 An Object Modeling Technique for Conceptual Design M. Loomis, A. Shah & J. Rumbaugh (Calma Compagny) 2:00-3:00 Invited lecture Kristen Nygaard (University of Oslo) Session-7: SIMULATION Chairman: J. Vaucher (University of Montreal) 3:00-3:30 A Modeller's Workbench: Experiments in Object Oriented Simulation Programming W. Kreutzer (University of Canterbury) 3:30-4:00 Behavioral Simulation Based On Knowledge Objects Takeo Maruichi, Tesuya Uchiki and Mario Tokoro (Keio University) Session-8: INHERITANCE Chairman: Peter Wegner (Brown University) 4:30-5:00 Conformance, Genericity, Inheritance and Enhancement Chris Horn (Trinity College Dublin) 5:00-5:30 Inheritance and Subtyping in a Parallel Object Oriented Language Pierre America (Philips Research Lab) 5:30-6:00 On Some Algorithms for Multiple Inheritance In Object Oriented Programming R. Ducourneau (SEMA-METRA) & M. Habib (LIB) ************** Reserve Papers ************** Principles for Programming Concurrent Object-Oriented Systems Gul Agha (MIT) FORK: A System for Object - and Rule - Oriented Programming C. Beckstein, G. Goerz and M. Tielemann (University of Erlangen-Nurnberg) Overview of a Parallel Object Oriented Language CLIX Jin Hur and Kilnan Chon (Korea Advanced Institute of Science and Technology) ******************************************* Discussions Papers Wednesday, June 17 Chairman P. GLOES (University of Compiegne) ******************************************* 9:00-9:10 GALOPIN: un systeme oriente objet pour le demarrage automatique des unites chimiques R. Loubeyre (Rhone-Poulenc) & C. Melin (Universite de Compiegne) 9:10-9:20 Conception d'une base de connaissance orientee objet pour l'EAO de la geometrie Eugene Chouraqui & Carlo Inghilterra (CNRS Marseille) 9:20-9:30 Microprogramming in Object Oriented Style: An experience with a Lisp co-processor Jean-Jacques Codani & Louis Audoire (GIPSI-SM90 INRIA) 9:30-9:40 An Application of Object-Oriented Programming to Petri Net Models of Discrete Event-Driven Simulation Cydney Minkowitz and Peter Henderson (University of Stirling) 9:40-9:50 A Novel Rule Based Facility For Smalltalk Wilf LaLonde (Carleton University - Canada) 9:50-10:00 Integrating Prolog in the Smalltalk/V Environment Mike Teng (Digitalk Inc) ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Tue Mar 10 00:48:46 1987 Date: Tue, 10 Mar 87 00:48:40 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #74 Status: R AIList Digest Monday, 9 Mar 1987 Volume 5 : Issue 74 Today's Topics: Query - Checking Rule-Based Expert Systems & Public-Domain Expert System Request, Source - Eliza, Doctor, Parry, Ractor, etc, Expert Systems - Explanation & Analysis of Unknown Data, Philosophy - Self-Recursive Functions == Consciousness ---------------------------------------------------------------------- Date: Sun, 8 Mar 87 9:31:01 WET From: "G. Joly" (Birkbeck) Subject: Checking Rule-Based Expert Systems (Info Request). We are at the start of a project which is examining the area of validation and verification of rule-based expert systems. CHECK [1] and ONCOCIN [2] are the two major systems of which we are aware. Are there any others? How isomorphic are rule-based systems; can these and other techniques be applied in general? Are any other (e.g. database) techniques applicable? Thanks in advance for any pointers and information, Gordon Joly, Dept. of Computer Science, Birkbeck College, University of London. ARPA: gjoly@cs.ucl.ac.uk BITNET: UBACW59%uk.ac.bbk.cu@AC.UK UUCP: ...{seismo,decvax,ucbvax}!mcvax!ukc!uk.ac.bbk.cs!gordon [1] T.A.Nguyen, W.A.Perkins, T.J.Laffey and D.Pecora, "Checking an Expert Systems Knowledge Base for Consistency and Completeness"., IJCAI 1985, pp 375-378. [2] M.Suwa, C.Scott and E.H.Shortliffe, "An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System", The AI Magazine, Fall 1982, pp 16-21. ------------------------------ Date: 6 Mar 87 12:20:04 GMT From: ulysses!sfmag!sfsup!saal@ucbvax.Berkeley.EDU (S.Saal) Subject: Expert System Request I am trying to set up a seminar to review expert systems. Is there any public domain expert systems available that I could get my hands on so that we can walk through the source code? Beggers can't be choosers so I really don't care what language it is in. All I want is source (commented code would be nicer, though :-). Please reply by E-MAIL to Sam Saal ..!attunix!sfbai!saal ------------------------------ Date: 6 Mar 87 16:00:12 GMT From: copp@bellcore.com (David H. Copp) Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ... "The Policeman's Beard is Half Contructed," authored by Racter (with a little help from William Chamberlain), Warner Books Inc., 666 Fifth Avenue, New York, NY 10103, USA. First printing Oct 1984. This is a new publisher. You may have to write directly to Warner Books, P.O. Box 690, New York, NY 10019, USA. They ask for a check for the list price ($9.95) plus $0.75 per order and $0.50 per copy. This is not a technical book. It tells you very little about Racter. It is an amusing addition to your coffee table. Martin Gardner (or was it Hofstedder?) devoted two or three pages to Racter about three years ago (Scientific American). Good article. The program itself can be purchased, IBM PC format, for about $75--see the SA article.) -- David H. Copp (201) 829-4337 bellcore!copp ------------------------------ Date: 6 Mar 87 21:58:32 GMT From: jennifer!lyang@sun.com (Larry Yang) Subject: Re: dear abby.... In article <886@rpics.RPI.EDU> yerazuws@rpics.RPI.EDU (Crah) writes: >In article <178@arcsun.UUCP>, roy@arcsun.UUCP (Roy Masrani) writes: >> >> Dear Abby. My friends are shunning me because i think that to call >> a program an "expert system" it must be able to explain its decisions. >> "The system must be able to show its line of reasoning", I cry. They >> say "Forget it, Roy... an expert system need only make decisions that >> equal human experts. An explanation facility is optional". Who's >> right? In medical decision systems, the ability to explain the decision is very important. I believe that most medical 'expert' systems (MYCIN and INTERNIST come to mind) have a 'why' or 'explain' feature. My understanding is that these systems were to have applications in teaching, and such a feature would help medical students understand the medical decision-making process. But beyond the educational application, it seems that an 'expert' system will gain greater acceptance if it had an 'explain' feature. Would you accept a solution that some black-box, electronic oracle offered you, without any why or wherefore? Imagine two doctors diagnosing a condition. Suppose one were asking the other for his/her advice. Would the first doctor accept just a diagnosis from the second, or would he/she also ask for an explanation? ================================================================================ --Larry Yang [lyang@sun.com,{backbone}!sun!lyang]| A REAL _|> /\ | Sun Microsystems, Inc., Mountain View, CA | signature | | | /-\ |-\ /-\ "Build a system that even a fool can use and | <|_/ \_| \_/\| |_\_| only a fool will want to use it." | _/ _/ ------------------------------ Date: 5 Mar 87 17:39:06 GMT From: mcvax!ukc!cheviot!rosa@seismo.css.gov ( U of Dundee) Subject: Re: dear abby.... Dear Abby, My problem is that I think I may be schizophrenic.. When I say "expert system" I mean a program which advises or searches for solutions in a restricted domain of data. Since I am British this program would be written at first in prolog. When others use the phrase "Expert System" they mean some kind of all singing, all dancing REAL WORLD EXPERT ... a human being not a program.... I have the same mismatch problem with the words "knowledge based", "knowledge aquisition", "intelligent", and most importantly with explanations... If a friend wants an "expert system" to help diagnose faults in cooking(say), I write a program to choose oven settings and help out with sensible advice for drooping souffles. When they ask for "the reason why" should I have written a huge explanation database instead of relying on the programming language internal logic control??????? Abby please help me decide if I should use a different, more technical phrase like advice giving database program instead of the confusing and misunderstood "expert system" or join a less demanding profession like brain surgery? yrs, a sad hacker. ------------------------------ Date: Sat, 7 Mar 87 17:23:29 est From: zs01#@andrew.cmu.edu (Zalman Stern) Subject: Re: Dear Abby, Analysis of unknown data. Dear Abby: Explanation of results in an expert system should be viewed as a method of communication between intelligent entities. Conventional groups of human experts tend to fail very badly when nobody tells anybody else what is going on. If you expect anything different to happen with artificial experts, you are very disillusioned. I think explanation facillities must be designed into the standard interface a program uses to communicate with humans and other expert systems. Of course teling too much tends to bore people also... Why not view AI as a chance to fix some of the bugs in human communication? Analysis of unknown data: I guess the idea here is to come up with an expert version of the UNIX file program. (file is a program which is executed like "file core" and it tells you "core: core file from 'loseprog'") The file program is written using very ad hoc techniques. It knows about all the magic numbers commonly used in a UNIX system, about keywords for common languages, patterns that occur in various kinds of text... As you can guess, it assumes a lot. One of the first things to realize is that there are files for which your system is not going to be able to come up with any useful information. Try feeding it 156MB of perfectly random numbers for example. One must also figure out what kind of explanations this system is going to give. In the organization category do you want explanations of the form "The file is columnized data." or "This file is in the proper format of a doctoral disertation in Computer Science at Carnegie Mellon University?" Once the program has figured out what the file is, it can easily extract the "representation, organization, and content" of the file using information from its knowledge base. So the problem has become one of designing a pattern matcher, and coming up with a knowledge base that knows about all kinds of files. Optionally, the program could try and deduce all the information desired from the file, but I think that would be much more difficult to do. Here is one way to approach this problem: Design a number of representations of a file. Examples of these are: - ASCII text in line format. (i.e. like your favorite editor does it). - A numerical dump of the file. Also, there are many formats specific to certain programs. For these, the representation is derived from firing up the appropriate program on the file. For example, if you are trying to classify a system executable, you will want to run the system debugger (or disassembler) on the file. There is an assumption here that files don't exist in a vacuum. If they did, they would be useless. Now that this is done, you are ready to start building a knowledge base. To do this you want to have a driver program that allows an expert to examine files and enter information into the system. The driver progam will need enoug "intelligence" to ask the expert why he did certain things. Of course you can have humans analyze the experts answers and encode them appropriately. Then just get a bunch of experts, and a large file system and let them hack at it... I think this may even be doable, but I doubt it would be worthwhile. Have I made too many assumptions? Is this general enough? Is this what you consider automated? Sincerely, Zalman Stern ARPA: zs01#@andrew.cmu.edu Disclaimer: I am not involved in any kind of AI research and never have been. ------------------------------ Date: Sun, 8 Mar 87 00:30:56 EST From: mckee%corwin.ccs.northeastern.edu@RELAY.CS.NET Subject: self-recursive functions == consciousness While trying to come up with some "characteristically lisp" code to benchmark different implementations with (since we didn't have R.Gabriel's collection at the time), the following argument occurred to me: Suppose one has two large, intelligent systems, both of which can speak English, know about baseball and politics, and can accurately report on their past experiences, yet one is conscious and the other is not. If we take away language, baseball, politics, and the past, we are left with two *content-free* mental systems, i.e. pure structure. One structure exhibits the properties of consciousness, while the other does not. What are the differences in structure that cause the differences in properties? Can we write them in Lisp? Since we have by hypothesis removed all content from the systems, we are left with no data, but pure control flow, i.e. an unnamed lambda expression. Now the intuitive essence of consciousness seems to be self- reference. Without self-reference we have only unidirectional entropy-processing, which is done by everything. Can one write a content-free self-referential function, which gets its work done by pure control flow and lambda-binding? How about: (LAMBDA (self n) (COND ((ZEROP n) 0) (T (+ n (self self (1- n)) )))) The function this expresses is very simple because what's important is how it's expressed, not what it does. In order to work, it has to be called with itself and an integer as arguments; it then computes the sum of the first n integers. But it can do this without touching the static part of its environment, not by define's, defun's, set's, or anything else. (It does require a quote to get it started.) It is completely dynamic, as pure consciousness seems to be. The key feature of self-recursive functions like this appears to be the applicative loop that occurs when the function is a lambda- expression that (1) has been given itself as an argument and (2) calls itself (i.e. its arg) recursively using the self-arg in the same argument position. A general pattern for this looks like: (LAMBDA (A1 ... Ai ... An) ... (Ai Bi ... Ai ... Bn) ...) where any corresponding Aj and Bj pair may be identical, but at least one Bj must be different from its Aj or an infinite recursion will result. (There are other conditions on how they have to differ which are irrelevant as long as they guarantee termination.) Again, this only works if it is initiated with itself as argument Ai. It seems to me that this pattern captures the only aspect of consciousness that is writable in lambda calculus and essential for consciousness while not essential for not-necessarily-conscious activities such as speech, memory, vision or problem-solving. The fact that it's a pattern explains a lot of the trouble people have with consciousness, since its elements could be broken apart, scattered, renamed, and passed through other functions before being resurrected as one funcall among many. (In a system as complex as a human mind, make that "many, many, many, many"...) A function that recognizes self-recursion in an arbitrary function definition is not small even in a tiny language, since it has to be able to track the components of the critical argument through potential decomposition and reconstruction, quoting, lambda- binding and other tortures. The recognition function for a real AI language like common lisp will be even bigger, since it will have to deal with macros, reader modifications and STRING/MAKE-SYMBOL pairs. It may even turn out to not be a computable function, for all I can tell. It seems to me that there are four classes of reasonable objections to this claim that self-recursion is the essence of consciousness: 1. "Consciousness is an ill-posed problem" in the sense that Tomaso Poggio has been talking about in vision. There's no unitary, simple, elegant way of expressing what we're talking about. I'm unhappy with this because it means we'll never "understand" consciousness, though we may be able to construct large more-or-less-convincing systems that appear to act as if they were conscious. 2. "Consciousness cannot be expressed in pure lisp." A strong claim, since accepting it requires modification of Church's Thesis, and claiming that there are material objects that {_ perform computations that cannot be expressed in the lambda calculus. I'm not entirely opposed to this, since one can envision massively parallel systems becoming so large that it might be useful to start thinking in terms of "density of computation" and taking the limit as the density approaches continuity in the same way the rational numbers approach the reals. Physically, you run into quantum limitations first, but continuous computation may be theoretically interesting. (No, I don't think this is the same as analog computation, but I can't explain why.) 3. "Consciousness can be expressed in lisp, but the pattern shown here isn't it." Please show us the correct answer. But remember Occam's razor: in science, small is beautiful. 4. "Consciousness is an illusion. It can't be expressed in lisp because it doesn't exist." This is my favorite. Steven Harnad's colleague Julian Jaynes has written a fascinating book which argues that consciousness first appeared on the planet less than 3000 years ago. I see no reason why consciousness couldn't vanish once we learn how to avoid spending valuable mental resources on introspection. It of course remains to be explained why consciousness has been such a powerful illusion. I apologize if I'm rediscovering ground already covered in this forum; I've only been reading the AIlist for a few months. This is about all I have to say on the subject, so if the moderator decides to distribute this, I hope he doesn't mind if I request that responses be sent to the net, not to me. "...a region of sight, of sound, of mind. Submitted for your consideration, from" - George McKee College of Computer Science Northeastern University ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Fri Mar 13 02:15:53 1987 Date: Fri, 13 Mar 87 02:15:45 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #75 Status: R AIList Digest Thursday, 12 Mar 1987 Volume 5 : Issue 75 Today's Topics: Seminars - Artificial and Natural Intelligence (UCB) & Fluid Concepts and Creative Analogies (UMich) & Representational Alignment (UCB) & Induction, Knowledge, and Expert Systems (GMR) & Search and Reasoning in AI (CMU) & Multilisp (CMU) ---------------------------------------------------------------------- Date: Mon, 9 Mar 87 11:22:39 PST From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science Program) Subject: Seminar - Artificial and Natural Intelligence (UCB) Berkeley Cognitive Science Program Presents a Special IDS 237B Seminar Time: Thursday, March 19, 11:00-12:30 Place: Building T-4, Room 200 Speaker: Klaus Fuchs-Kittowski, Dept. of Theory and Organization of Science, Humboldt University, Berlin, GDR Visiting Professor, John Hopkins University Chairman, Working Group 1 of TC9 of IFIP Computers Title: ``Philosophical Views and Methodological Assumptions Regarding the Relationships between Artificial and Natural Intelligence" ABSTRACT Computers are general agents of change in the information revo- lution in the same way that Watt's steam engine revolutionized industry. The problem of defining the relationship between human and artificial intelligence is central to the problem of applying computer power in a humane way in society. Resolution of these questions requires application of multidisciplinary approaches to what has traditionally been a mechanistic approach. The multidisciplinary approach requires understanding the unity of the syntax, semantics, and effects of information. ------------------------------ Date: Sun, 8 Mar 87 17:25:12 est From: mm@farg.umich.edu (Melanie Mitchell) Subject: Seminar - Fluid Concepts and Creative Analogies (UMich) WEEKLY AI SEMINAR, UNIVERSITY OF MICHIGAN, ANN ARBOR SPEAKER: Melanie Mitchell, EECS Dept., University of Michigan DATE: Tuesday, March 17 TIME: 4:30 pm PLACE: 1303 EECS Building (North Campus) TITLE: "Fluid Concepts and Creative Analogies: A Theory and its Computer Implementation" Abstract This talk is based on research done by Douglas R. Hofstadter, Melanie Mitchell, and Robert M. French. We describe the principles of Copycat, a computer model of how humans use concepts fluidly in order to create analogies. Our model is centered on the Slipnet, a network of overlapping concepts whose shapes are determined dynamically by the situations faced by the program. Reciprocally, the state of the Slipnet controls how Copycat perceives situations. The heart of what Copycat does, given two situations, is to produce a worlds-mapping: a coarse-grained mental correspondence between the situations, involving two interdependent and mutually consistent facets: an object-to-object mapping realized in structures called bridges, and a concept-to-concept mapping realized in structures called pylons. Each pylon expresses a so-called conceptual slippage, borrowed from the slipnet. Taken together, the slippages constitute a recipe for translating actions in one situation into their analogues in the other. Through the "coattails effect", slippages can induce closely related slippages, allowing deeper and more subtle analogies to be produced than would otherwise be possible. For copies of a paper describing this research, send messages to mm@farg.umich.EDU ------------------------------ Date: Wed, 11 Mar 87 10:36:25 PST From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science Program) Subject: Seminar - Representational Alignment (UCB) SESAME Colloquium 10/16 Jeff Shrager Xerox Palo Alto Research Center Monday 16 March 1987 2515 Tolman Hall 4:00 pm Abstract Analogy and conceptual combination deal with more than one knowledge structure. Only structures which are based on the same terms and relations can generally be combined by these mechanisms. In order to make conceptual combination work smoothly with large representationally heterogeneous knowledge bases, I am working toward automated high-level to high-level representational alignment. My approach is based upon the intuitive model of how two speakers would communicate if they had incompatible understandings of some domain. The process involves "grounding" terms and relations in the high-level representations into common lower-level representations and then constructing constraints based upon the structure of this grounding trace. This talk will focus on the cognitive motivations for grounding and ground-directed alignment and on the cognitive implications of the requirements imposed on mental models by ground-directed alignment. Grounding highlights the difference in the content terms of mental models: grounded terms versus ungrounded terms, which have a counterpart in the difference between empirical and derived terms in qualitative mental models. I show how the grounding of such models into animations gives us a concrete handle on the relationship between imagery and the symbolic processes. ------------------------------ Date: Wed, 11 Mar 87 15:55 EST From: "R. Uthurusamy" Subject: Seminar - Induction, Knowledge, and Expert Systems (GMR) Seminar at the General Motors Research Laboratories in Warren, Michigan. Friday, March 20, 1987 at 10 a.m. INDUCTION, KNOWLEDGE, and EXPERT SYSTEMS J. ROSS QUINLAN Head, School of Computing Sciences New South Wales Institute of Technology, Sydney, Australia ABSTRACT This general talk examines inductive inference as a knowledge acquisition methodology, both from the perspective of the performance characteristics of the knowledge so acquired and its intelligibility. A relatively simple class of induction methods that generate decision trees for classification tasks is outlined and illustrated. A case study in which this approach was used to generate diagnostic knowledge in the domain of thyroid assays is presented, and the performance of the decision trees is compared with that of a conventional expert system constructed by interviewing endocrinologists. Finally, recent work in which decision trees are re-expressed as collections of production rules has been found to improve both the accuracy and comprehensibility of the inductively acquired knowledge. Non-GMR personnel interested in attending please contact R. Uthurusamy [ samy@gmr.com ] 313-986-1989 ------------------------------ Date: 9 Mar 87 16:59:31 EST From: Patty.Hodgson@isl1.ri.cmu.edu Subject: Seminar - Search and Reasoning in AI (CMU) AI SEMINAR TOPIC: Search and Reasoning in AI SPEAKER: Herb Simon PLACE: Wean Hall 5409 DATE: Tuesday, March 10, 1987 TIME: 3:30 pm ABSTRACT: What is the relation between the search paradigm in AI and the reasoning or deductive paradigm implicit or explicit in most theorem proving programs, PROLOG, and Nilsson's text?? The talk will undertake to show that these two points of view cannot be distinguished on logic grounds but that they represent very different heuristic viewpoints about how AI systems are to be constructed, and about the relation of these systems to the "real world." The talk will develop and extend views published in Artificial Intelligence 28 21:7-29 (1983). ------------------------------ Date: 10 Mar 87 11:55:40 EST From: Karen.Olack@h.cs.cmu.edu Subject: Seminar - Multilisp (CMU) Speaker: Robert Halstead Date: March 16, 1987 Time: 2:00 p.m. Place: Wean Hall 8220 Topic: Multilisp: A Language for Parallel Symbolic Computing ABSTRACT Multilisp is an extension of Scheme with additional operators and additional semantics for parallel execution. These have been added without removing side effects from the language. The principal parallelism construct in Multilisp is the "future," which exhibits some features of both eager and lazy evaluation. Current work focuses on making Multilisp a more humane programming environment, on expanding the power of Multilisp to express task scheduling policies, and on measuring the properties of Multilisp programs with the goal of designing a parallel architecture well tailored for efficient Multilisp execution. Multilisp has been implemented, and runs on the shared-memory Concert multiprocessor, using as many as 27 processors. The implementation uses interesting techniques for task scheduling and garbage collection. The task scheduler helps control excessive resource utilization by means of an unfair scheduling policy; the garbage collector uses a multiprocessor algorithm modeled after the incremental garbage collector of Baker. The talk will briefly describe Multilisp, discuss the areas of current activity, and indicate the future direction of the project in the areas of language design, application development, and multiprocessor architecture. ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Fri Mar 13 02:16:10 1987 Date: Fri, 13 Mar 87 02:15:58 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #76 Status: R AIList Digest Thursday, 12 Mar 1987 Volume 5 : Issue 76 Today's Topics: Discussion Lists - AI-CHI & Info-1100/Bug-1100, Queries - Washington-Area TI Seminar & Chess Evaluator & AI bibliographies & 3-D Clustering Algorithms & Comparative Psychology of Intelligence ---------------------------------------------------------------------- Date: Mon, 9 Mar 87 11:00:38 PST From: wiley!sherman@lll-lcc.ARPA (Sherman Tyler) Subject: AI Lists You recently sent a message about existing mailing lists on ARPANET that related to AI. Not long ago, we started another list called AI-CHI to look at artificial intelligence applications to computer-human interaction. We would appreciate it if you could appropriately update your own list of AI lists with this item. The list is: wiley!ai-chi@lll-lcc.arpa and requests to be added to the list can be sent to: wiley!ai-chi-request@lll-lcc.arpa Thanks very much. ------------------------------ Date: Mon 9 Mar 87 21:52:30-PST From: Christopher Schmidt Subject: Info-1100/Bug-1100 For the record, Info-1100 and Bug-1100 have been merged into one list; Info-1100. --Christopher ------------------------------ Date: 9 Mar 87 09:27:00 EST From: "WHITE::PSOTKA" Reply-to: "WHITE::PSOTKA" Subject: Washington-Area TI Seminar? Is anyone in the greater Washington D.C. area going to be showing the TI AI seminar in a semi-public facility? I would like to attend. Psotka (202)274-5540 ------------------------------ Date: 10 Mar 87 14:43:09 GMT From: mcvax!ukc!its63b!gvw@seismo.css.gov (G Wilson) Subject: HHelp needed with computer chess I am writing a chess program to run on a Meiko Computing Surface, a highly parallel MIMD machine containing 40 transputers. I started by converting the Free Software Foundation's GNUChess program, and I have move generation and tree search fairly well in hand, but I desperately need a better board evaluation function. All of the literature I have been able to locate on computer chess describes some of the features a good function should have, but no-one actually lists a set of numerical weights! Does anywhere out there in net.land have an old chess program running on an Apple-II or a BBC Micro or even source code for the standard UNIX chess program that has an evaluation function I could use? Any language will do. Failing that, does anyone have pointers to literature which doesn't just talk about such functions, but actually lists one or two (or three, or four, or ...)? Much appreciated. Greg Wilson ------------------------------ Date: Wed, 11 Mar 87 17:17:42 EST From: Raul.Valdes-Perez@B.GP.CS.CMU.EDU Subject: AI bibliographies Does anyone have a file containing all the titles of papers published in the leading AI sources e.g. Journal, IJCAI, AAAI, ECAI etc.? It would be nice to do a string search for certain topics and find relevant papers instantly. ------------------------------ Date: Mon, 09 Mar 87 18:31:38 n From: DAVIS%EMBL.BITNET@wiscvm.wisc.edu Subject: 3D Clustering algorithms The subject just about sums it up......anyone out there in the 'lectronic village overly proud, or overly knowledgeable, or even just familiar with clustering algorithms for use in three dimensions ? That is to say, I have a bunch of points in a 3D space, and I want to cluster them. Simple huh ? Tell me how, or tell me how to find out how......replies directly to me, or post them on the list. with thanks, Paul Davis Euopean Molecular Biology Laboratory, Postfach 10.2209 6900 Heidelberg West Germany bitnet: davis@embl.bitnet uucp: ...psuvax!embl.bitnet!davis petnet: homing pigeons to.... "a time for dreams, a time for sleep, a time for love .... its now!" [What makes three-space special? Any similarity or dissimilarity metric that works in three dimensions should work in N dimensions. The really interesting cases are those where no reasonable weighting exists for combining distances in the different dimensions. Any of the major subroutine packages -- BMD, SPSS, etc. -- have clustering routines and associated documentation. Euclidean space is generally assumed, which causes problems with circular scales such as hue in a color space. (One heuristic for color spaces is to linearize the usual 256^3 cells by tracing through the space with a fractal curve, then search for clusters in the 1-D result.) Other 3-D spaces are best analysed in terms of direction cosines for vectors to the points from some origin. Statistical metrics based on within-cluster and between-cluster variances are optimal for some applications, but gravitational or potential-based models are better in others. ISODATA is a time-honored heuristic method for growing and splitting clusters, but is only suitable for circular clusters in isometric spaces. Zahn's method of analyzing minimal spanning trees is one way of overcoming the common faults (e.g., chaining or lack thereof) of heuristic approaches. The book on Pattern Recognition and Image Processing by Duda and Hart offers an easy introduction to some of the statistical and heuristic methods. Other pattern recognition books are more thorough. Clustering is still a black art, though, and you are probably best off getting a commercial package and trying a few of the options to get a feel for what works with your data. -- KIL] ------------------------------ Date: Wed, 11 Mar 87 23:17:17 est From: Stevan Harnad Subject: Comparative Psychology of Intelligence: BBS Call for Commentators The following is the abstract of a forthcoming article on which BBS [Behavioral and Brain Sciences -- An international, interdisciplinary Journal of Open Peer Commentary, published by Cambridge University Press] invites self-nominations by potential commentators. (Please note that the editorial office must exercise selectivity among the nominations received so as to ensure a strong and balanced cross-specialty spectrum of eligible commentators. The procedure is explained after the abstract.) ----- THE COMPARATIVE PSYCHOLOGY OF INTELLIGENCE Euan M. Macphail Department of Psychology University of York Heslington, York YO1 5DD United Kingdom Recent decades have seen a number of influential attacks on the comparative psychology of learning and intelligence. Two specific charges have been that the use of distantly related species has prevented making valid evolutionary inferences and that learning mechanisms are species-specific adaptations to ecological niches and hence not properly comparable between species. It is argued here that investigating distantly related species may allow valuable insights into the structure of intelligence and that the question of whether learning mechanisms are niche-specific is one that can only be answered by comparative work in "non-natural" situations. The problems involved in the definition and assessment of intelligence are discussed. Experimental work has not succeeded in demonstrating differences in intellect among nonhuman vertebrates; hence the null hypothesus that there exist no differences in intellect amongst nonhuman vertebrates should be adopted. The superiority of human intelligence stems from our possession of a species-specific language-aquisition device. One implication of the null hypothesis is that general problem-solving capacity is independent of niche-specific adaptations. A second implication is that problem-solving may involve relatively simple mechanisms: Association formation in particular may play a central role in nonhuman intelligence, allowing the successful detection of causal links between events, causality being a common constraint to all niches. ----- This is an experiment in using the Net to find eligible commentators for articles in the Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal of "open peer commentary," published by Cambridge University Press, with its editorial office in Princeton NJ. The journal publishes important and controversial interdisciplinary articles in psychology, neuroscience, behavioral biology, cognitive science, artificial intelligence, linguistics and philosophy. Articles are rigorously refereed and, if accepted, are circulated to a large number of potential commentators around the world in the various specialties on which the article impinges. Their 1000-word commentaries are then co-published with the target article as well as the author's response to each. The commentaries consist of analyses, elaborations, complementary and supplementary data and theory, criticisms and cross-specialty syntheses. Commentators are selected by the following means: (1) BBS maintains a computerized file of over 3000 BBS Associates; the size of this group is increased annually as authors, referees, commentators and nominees of current Associates become eligible to become Associates. Many commentators are selected from this list. (2) The BBS editorial office does informal as well as formal computerized literature searches on the topic of the target articles to find additional potential commentators from across specialties and around the world who are not yet BBS Associates. (3) The referees recommend potential commentators. (4) The author recommends potential commentators. We now propose to add the following source for selecting potential commentators: The abstract of the target article will be posted in the relevant newsgroups on the net. Eligible individuals who judge that they would have a relevant commentary to contribute should contact the editor at the e-mail address indicated at the bottom of this message, or should write by normal mail to: Stevan Harnad Editor Behavioral and Brain Sciences 20 Nassau Street, Room 240 Princeton NJ 08542 (phone: 609-921-7771) "Eligibility" usually means being an academically trained professional contributor to one of the disciplines mentioned earlier, or to related academic disciplines. The letter should indicate the candidate's general qualifications as well as their basis for wishing to serve as commentator for the particular target article in question. It is preferable also to enclose a Curriculum Vitae. (This self-nomination format may also be used by those who wish to become BBS Associates, but they must also specify a current Associate who knows their work and is prepared to nominate them; where no current Associate is known by the candidate, the editorial office will send the Vita to approporiate Associates to ask whether they would be prepared to nominate the candidate.) BBS has rapidly become a widely read read and highly influential forum in the biobehavioral and cognitive sciences. A recent recalculation of BBS's "impact factor" (ratio of citations to number of articles) in the American Psychologist [41(3) 1986] reports that already in its fifth year of publication (1982) BBS's impact factor had risen to become the highest of all psychology journals indexed as well as 3rd highest of all 1300 journals indexed in the Social Sciences Citation Index and 50th of all 3900 journals indexed in the Science Citation index, which indexes all the scientific disciplines. Potential commentators should send their names, addresses, a description of their general qualifications and their basis for seeking to comment on this target article in particular to the address indicated earlier or to the following e-mail address: {allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad harnad%mind@princeton.csnet [Subscription information is available from Harry Florentine at Cambridge University Press: 800-221-4512] ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Sat Mar 14 19:15:39 1987 Date: Sat, 14 Mar 87 19:15:28 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #77 Status: R AIList Digest Friday, 13 Mar 1987 Volume 5 : Issue 77 Today's Topics: Queries - Addresses & Genetic Algorithms & Planning and Scheduling & TI Satellite Symposium Locations, Funding - AFOSR Announcement, Games - ICCA Journal, Expert Systems - Checking Rule-Based Expert Systems, Application - Analysis of Unknown Data ---------------------------------------------------------------------- Date: Tue 10 Mar 87 14:39:19-EST From: John C. Akbari Subject: whereabouts Does anyone have email or snail mail addresses for any of these people? They are some Brits who have published very interesting work in knowledge acquisition for expert systems. any assistance will be appreciated. Anna Hart Alison Kidd Lisanne Bainbridge Margaret Welbank ad...THANKS...vance! john c akbari ARPANET & Internet akbari@CS.COLUMBIA.EDU BITnet akbari%CS.COLUMBIA.EDU@WISCVM.WISC.EDU uucp & usenet ...!seismo!columbia!cs!akbari DECnet akbari@cs PaperNet 380 riverside drive, no. 7d new york, new york 10025 usa SoundNet 212.662.2476 ------------------------------ Date: Thu, 12 Mar 87 18:08 EST From: Olasov@MIT-MULTICS.ARPA Subject: Network_addresses_of_Contributors Hello, This is a response to several bibliographical entries in the AI-List forum on the ARPANET. I'm interested in sending network mail to a number of individuals who were contributors of one or more entries in the AI-List, however I don't have their network mail stops. Can you help me out with this, or if you don't have their network addresses, could you forward this letter to someone who might? The individuals I wish to contact are: John S. Gero or John Radford or P. Hing authors of New Rules of Thumb from Computer Aided Structural Design: Aquiring Knowledge for Expert Systems Proceedings CADD-84 UK 1984 AIME Hitoshi Furuta King Sun Tu Minhai Bambuceanu, author of Knowledge Engineering in CAD North Holland Daniel Rehak H. Craig Howard authors of Interfacing Expert Systems with Design Databases in Integrated CAD Systems P. Haren M. Montalban authors of Prototypical objects for CAD systems Dennis J. Nicklaus Siu S. Tong creators of Engineous: A Knowledge Directed Computer Aided Design Shell If you know the network address of even one of these individuals, I'd appreciate it more than I can express if you would send it to me. Thanks. Best Regards, Ben Olasov [King-Sun Fu died in April of '85, so you may have difficulty reaching him. John Gero is with the Dept. of Architectural Science at the University of Sydney (Sydney 2006 Australia), and can probably be reached as "munnari!archsci.su.oz!john"@seismo.CSS.GOV. (Note the lower-case seismo.) Most contributors to AIList can be reached via the From address in the message; I can help interpret it if you send me a copy. -- KIL] ------------------------------ Date: 11 Mar 87 00:57:31 GMT From: amdcad!amd!intelca!mipos3!omepd!uoregon!hp-pcd!hpcvlo!karen@ucbv ax.Berkeley.EDU (Karen Helt) Subject: Genetic Algorithms I am investigating genetic algorithms as they relate to machine learning and in particular classifier systems. I hope to do my master's thesis in this area. I am trying to locate literature in this area. Does anyone know how I can get a copy of the "Proceedings of an International Conference on Genetic Algorithms and Their Applications,1985"? Also, it appears that a lot of work on genetic algorithms has been done at the University of Michigan. There are a number of Ph D theses of Univ. of Michigan students referenced in the articles I have found. Is Univ. of Michigan on the net? Will someone there please contact me and tell me how I can get copies of some of the theses? I would appreciate any help and information anyone can give me. Thanks. Karen Helt Hewlett-Packard Company Corvallis Workstation Operation Corvallis, Oregon part-time graduate student at Oregon State University hplabs!hp-pcd!karen ------------------------------ Date: Thu, 12 Mar 87 15:03:40 est From: nancy@grasp.cis.upenn.edu (Nancy Orlando) Subject: Planning and scheduling survey I have recently begun a project to examine the current techniques and capabilities of planning and scheduling systems. This covers a wide range of potential techniques and implementations; the systems of interest can range from robotic task planners to mission planners to job shop schedulers, using structures ranging from expert systems to classical programs to neural nets, using techniques ranging from means-ends analysis to constraint propagation to simplex algorithms. Pointers to any systems, either from the literature or work currently in progress, would be appreciated. I particularly am interested in acquiring information concerning the problem domain, the structure and technique(s) used aspects of the domain of the system that lead to the choice of structure and techniques, the strengths and weaknesses of the system, and an opinion as to the portability of the system to other domains. Maybe its deja vu, but I seem to recall another recent request to AIList concerning planning systems. A pointer to that source would also be appreciated. Results of this survey can be posted to the net if there is sufficient interest. USmail would be appreciated, as my net address is capricious: Nancy Sliwa MS 152D NASA Langley Research Center Hampton, VA 23665-5225 An E-mail address, if absolutely necessary: nancy%upenn-grasp@upenn Much thanks! ------------------------------ Date: 12-Mar-87 16:13:58 From: Dan Cerys Subject: TI Satellite Symposium locations A number of people have been posting queries about the the viewing locations for the third Texas Instruments Satellite Symposium on Artificial Intelligence. There are two ways that a person can "attend" the symposium. 1) If you can receive satellite video broadcasts, TI will provide the information you need to set your location up as viewing site. 2) There are a number of public viewing locations around the world. These are free unless the location is sponsored by another organization (eg, IEEE). Most of these locations require advance registration. In either case, there is a toll-free number you can call to receive more information and/or register at a viewing location: (800) 527-3500. (I'm not sure if this works for those outside of North America). I have only few details on the conference. It is titled "AI Productivity Roundtable" and will be held on April 8, 9:00 EST - 13:00 EST, followed by a 1 1/2 hour condensation of the 2nd Symposium beginning at 14:00 EST. ------------------------------ Date: 25-FEB-1987 14:44 From: GILES@AFSC-HQ.ARPA Subject: AFOSR Announcement [Forwarded from the Neuron Digest.] PROGRAM ANNOUNCEMENT: NEURAL COMPUTING AND PROCESSING The Air Force Office of Scientific Research (AFOSR) announces a new program of support for basic research on the computational aspects of neural networks. Research that could yield computational neural models of information processing, learning, and cognition in complex biological systems is specifically encouraged. AFOSR is interested in multidisciplinary theoretical and empirical approaches. Research focused on neural architectures subserving learning and cognition or on computational aspects of neuromorphic structures and systems is also of interest. Research proposals are now being accepted by AFOSR. All proposals received before July 1, 1987 will be considered for the first cycle of support to begin in October. Support from AFOSR is typically provided as multi-year grants or contracts. FOR ADDITIONAL INFORMATION CONTACT: Dr. C. Lee Giles Architectures and Computation 202-767-4931 GILES@AFSC-HQ.ARPA Dr. William O. Berry Life Sciences 202-767-5021 Dr. Vincent Sigillito Artificial Intelligence 202-767-5028 Dr. John F. Tangney Life Sciences 202-767-5021 TANGNEY@AFSC-HQ.ARPA AIR FORCE OFFICE OF SCIENTIFIC RESEARCH BOLLING AFB, BLDG 410 WASHINGTON, DC 20332-6448 ------------------------------ Date: Tue, 10 Mar 87 14:42:35 EST From: @um.cc.umich.edu@umix.cc.umich.edu, Subject: ICCA journal Can you post this to mod.ai? Thank you. The December 1986 issue of the ICCA Journal is now available. The ICCA (International Computer Chess Association) produces a quarterly journal, organizes the triennial World Computer Chess Championship, strengthen ties and promote co-operation amoung computer chess re- searchers, etc. This month's issue contains: RESEARCH PAPERS: Fuzzy Production Rules in Chess, P.W. Frey Influence of Ordering on Capture Search, P. Bettadapur Computer Analysis of a Queen Endgame, E.A. Komissarchik and A.L. Futer REPORTS: ACM's 17th North American Computer Chess Championship The 6th World Microcomputer Chess Championship OTHER: Compressing Databases down to Micro Size, H. Zellner An example of QPvQ, K. Thompson A note on KBBK, H.J. van den Herick and I.S. Herschberg Swedish Rating List, G. Gottling as wells as reviews, conference announcements, etc. A total of 60 pages. ICCA memberships are $20 US per year. For more information, contact ICCA c/o Jonathan Schaeffer Department of Computing Science University of Alberta Edmonton, Alberta Canada T6G 2H1 ihnp4!alberta!jonathan ------------------------------ Date: Mon, 09 Mar 87 14:50:31 -0800 From: mcguire@aero2.aero.org Subject: Re: Checking Rule-Based Expert Systems (Info Request). We have been working in this area for a while. In addition to checking for completeness and consistency we analyze a rule-base for the "effectiveness" of its information. It is possible for rules or distinctions to appear to have meaning, but through faulty interaction they wind up never influencing the answers the system gives. This sort of interference is unbounded in scope. We have developed propagation style algorithms for finding ineffective information in simple types of rule bases. A paper on this work is almost ready for release. I can mail out copies then. Roderick McGuire The Aerospace Corporation Box 92957 Los Angeles, CA 90009 ARPA: mcguire@aerospace.aero.org ------------------------------ Date: 9 Mar 87 14:01:51 GMT From: Dave Stoffel Subject: Re: Dear Abby, Analysis of unknown data. >I guess the idea here is to come up with an expert version of the UNIX file >program. The problem with the `file' approach is that it assumes one has already a knowledge of the "files" he is attacking. So, this technique might become more and more useful, but only "might". >One of the first things to realize is that there are files for >which your system is not going to be able to come up with any >useful information. Try feeding it 156MB of perfectly random >numbers for example. Testing for randomness might be the first test; sure would save a lot of subsequent computing if it were random. >files. Optionally, the program could try and deduce all the information >desired from the file, but I think that would be much more difficult to do. Yep. It would be nice to take a goal-driven, top-down approach, but sometimes data-driven inference, e.g., auto-correlation, is what there is. >representation is derived from firing up the appropriate program on the file. >For example, if you are trying to classify a system executable, you will want >to run the system debugger (or disassembler) on the file. There is an >assumption here that files don't exist in a vacuum. If they did, they would >be useless. Their uselessness and whether they exist in a vacuum is an assumption. -- Dave Stoffel (703) 790-5357 seismo!mimsy!dave dave@Mimsy.umd.edu Amber Research Group, Inc. ------------------------------ Date: 11 Mar 87 18:38:32 GMT From: tektronix!sequent!mntgfx!franka@ucbvax.Berkeley.EDU (Frank A. Adrian) Subject: Re: analysis of unknown data In article <5681@mimsy.UUCP> dave@mimsy.UUCP (Dave Stoffel) writes: > > > What systematic methods and techniques would you apply to the > following problem? > > Determine the representation, organization, and content of a > "file" containing up to 156MB. There are no assumptions. The >methods and techniques applied must be automated (if not fully >automatic) and applicable to an unlimited supply of "files". Actually, there are several ways to approach this problem. It is a statement of finding out what is happenning inside a classical "black box". You can start by monitoring all requests and replies from the file, searching for patterns based on location of access and length of access. You can examine the bytes returning from the device to try to detect patterns. You can use a traffic analysis approach by find out what types of programs access this file at which times for a given purpose. You can go ask the NSA, CIA, and other intellegence agencies what they do when they try to crack a black box (though I doubt that they'd tell you :-). Finally, most boxes are not com- pletely black. In general, you can tell information by the location, size, etc. of a box. But unless the box is completely isolated (in which case, why are you all that interested in what it does?) you can always get some infor- mation, upon which you can make your own assumptions, can try experiments, and finally uncover the nature of an object. You might also try any good text on experimental methods to point you in the right direction. Frank Adrian Mentor Graphics, Inc. ------------------------------ Date: 12 Mar 87 21:47:26 GMT From: dave@mimsy.umd.edu (Dave Stoffel) Subject: Re: analysis of unknown data In article <564@franka.mntgfx.MENTOR.COM>, franka@mntgfx.MENTOR.COM (Frank A. Adrian) writes: > Actually, there are several ways to approach this problem. It is a statement > of finding out what is happenning inside a classical "black box". You can > start by monitoring all requests and replies from the file, searching for > patterns based on location of access and length of access. You can examine > the bytes returning from the device to try to detect patterns. You can use > a traffic analysis approach by find out what types of programs access this > file at which times for a given purpose. the "file" of 156MB is not exactly a black box. The traditional black box problem describes functions whose structure is not known. The "file" is data, not procedure. An unknown number of procedures may have participated in creation of the data. The "file" is sitting on my machine after being read off of a tape which an archeologist(sp?) dug up. What is the data? Maybe it is one logical file, maybe hundreds. If hundreds, maybe each one is a different type. Maybe the bytes on the tape are not ordered as logical files, but as physical blocks from some disk pak. Put it back together, so you can tell the archeologist what information is on the tape, so he learns something about the civilization which left it. Dave Stoffel (703) 790-5357 seismo!mimsy!dave dave@Mimsy.umd.edu Amber Research Group, Inc. ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Mon Mar 16 02:35:44 1987 Date: Mon, 16 Mar 87 02:35:36 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #78 Status: R AIList Digest Sunday, 15 Mar 1987 Volume 5 : Issue 78 Today's Topics: Queries - Printed Circuit Board Software & Toshiba Voice Recognition Chip & Expert System/CAD Interfaces, Funding - AFOSR Commendation, Jargon - Maths as a Science, Expert Systems - Explanations ---------------------------------------------------------------------- Date: 14 Mar 87 00:36:07 GMT From: ucsdhub!hp-sdd!ncr-sd!se-sd!rich@sdcsvax.ucsd.edu (Rich Hume) Subject: Printed Circuit Board Software Question: Can someone point me to (or better yet send me) some public domain software for doing printed circuit board layout? Even somewhat out of date source would be useful. Please send responses to me. Thanks for any info! Rich Hume Application Environment Products NCR Corp. UUCP: ...!ncr-sd!se-sd!rich ...!seismo!scubed/ ------------------------------ Date: 14 Mar 87 02:13:10 GMT From: hoptoad!gnu@sun.com (John Gilmore) Subject: Toshiba voice recognition chip A recent article in Newsbytes Japan mentions: Toshiba's Voice Recognition LSI -- Toshiba (Tokyo) has developed a powerful LSI for recognizing human speech. This new product recognizes a variety of spoken sounds with 95% accuracy. Toshiba plans to use this LSI for a voice input system for its word processors. I am interested in building a voice control system for my house, which will be fully wired for sound. Does anyone have further information about this chip (e.g. press releases, other mentions in the press, papers at conferences, or actual product numbers and specs)? -- John Gilmore {sun,ptsfa,lll-crg,ihnp4}!hoptoad!gnu gnu@ingres.berkeley.edu Love your country but never trust its government. -- from a hand-painted road sign in central Pennsylvania ------------------------------ Date: Sat, 14 Mar 87 15:40 EST From: Olasov@MIT-MULTICS.ARPA Subject: Expert_system/_CAD_interfaces I'm doing research on applications of various expert system techniques in architectural design , with emphasis on interfacing knowledge based systems with CAD systems. In my research, I've developed a number of shells external to the CAD system, that are written in LISP, and that use different entry points to the CAD system. I've used rule based pattern matching shells and binary discrimination networks. I've also tried writing shells for an IBM-PC CAD package called AutoCAD, which has an internal LISP interpreter, with interesting results. I expected that an interpreter resident within the CAD system should be a superior strategy to that of having an interface of an external shell to the CAD package. I found that in the case of AutoLISP however, the internal LISP interpreter in AutoCAD, memory requirements for even trivial pattern matching algorhythms usually proved to be too great (yes, even in the latest versions of AutoCAD). Also, AutoLISP functions represent a very small subset of a full Common LISP, which makes ES applications exceedingly difficult to write, as functions which would otherwise be primitively defined must be defined at the interpreter level, thus using much of the precious memory it has to allocate to function definitions. Generally, small applications were successful. I would be very interested to learn about the research and experiences of others who are using, or attempting to use, expert system applications in CAD, particularly for architectural design purposes. Cheers, Ben Olasov ------------------------------ Date: Fri, 13 Mar 1987 19:14 EST From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU Subject: AIList Digest V5 #77 Subject: AFOSR Announcement ragerj@nucsrl.UUCP (John Rager) writes: >Logic is a branch of mathematics. The last time I checked mathematics >was a science. Where did you check? We have no local index of official scientific subjects over here :-). Perhaps some US professor has mapped out the whole of knowledge and categorised it while we were all asleep :-). In English secondary education, the official policy is that Maths is NOT a science, as it does not rest on any empirical methods at all (empirical in the sense of observing the natural world, perhaps in a controlled experiment). Neither is applied maths a science, as the modelling process may involve abstracting intuitively and the return to the real problem domain also involves unobservable judgement. Whilst the only thing most people could need to know about epistemology is how to spell it, folk in AI need to get right to grips with it if their talk of 'Knowledge Representation/Elicitation' is to be anything more than one big amateur pose. Throw in some cognitive sociology and the faint-hearted will probably go back to chess games and tic-tac-toe (real everyday intelligence that) :-). -- Gilbert Cockton, Scottish HCI Centre, Ben Line Building, Edinburgh, EH1 1TN JANET: gilbert@uk.ac.hw.aimmi ARPA: gilbert%aimmi.hw.ac.uk@cs.ucl.ac.uk UUCP: ..!{backbone}!aimmi.hw.ac.uk!gilbert ------------------------------ Date: 6 Mar 87 19:18:37 GMT From: ssc-vax!bcsaic!michaelm@BEAVER.CS.WASHINGTON.EDU (Michael Maxwell) Subject: Re: dear abby.... In article <1147@sfsup.UUCP> saal@/guest5/saalUUCP (45444-AUG871-S.Saal) writes: >In article <178@arcsun.UUCP> roy@arcsun.UUCP (Roy Masrani) writes: >>Dear Abby. My friends are shunning me because i think that to call >>a program an "expert system" it must be able to explain its decisions. >>"The system must be able to show its line of reasoning", I cry. They >>say "Forget it, Roy... an expert system need only make decisions that >>equal human experts... > >...Once it is "in production" (the field) it may not >be as important to give an explanation every time. This is >particularly the case when the expert system is used to help do >some of the more mundane tasks on a very frequent basis. There >are 2 reasons for this. (1) the user may be able to agree >intuitively after deriving the answer - the machine has just >helped speed the process. OR (2) If a production ES has been >converted to a compiled language, the code to express the >rationale may be removed to speed up run time. I'm not an ES expert, but when I talk to a human expert in a field, I commonly ask "why?" or "what alternatives are there?" (which is the same thing for the user, I think, although perhaps not for the expert). This is even true in "mundane" or frequently performed tasks. An example is when I went to the AAA to ask what the best route was to drive from Seattle to Miami in early spring. Since I'm going to an expert for the solution, there's a reason, and almost by definition it's not routine. I may have asked them how to drive from A to B many times, but in this case I asked why they routed me the way they did, because I'm unsure of the weather conditions over passes in Montana and Colorado. If the ES is to not just "make decisions that equal human experts" but replace and/or augment a human, I would want to be able to ask it the same questions. Hence I think that while point (2)--by deleting explanation code we can speed up the run time system--may be true, it is beside the point (pun). If anything, it is an argument for faster hardware. Or maybe I'm just suspicious... -- Mike Maxwell Boeing Advanced Technology Center arpa: michaelm@boeing.com uucp: uw-beaver!uw-june!bcsaic!michaelm ------------------------------ Date: Wed, 11 Mar 87 18:02:33 GMT From: Vic Churchill Reply-to: Vic Churchill Subject: Re: Expert systems In article <8703040725.AA27188@ucbvax.Berkeley.EDU> KRULWICH@C.CS.CMU.EDU (Bruce Krulwich) writes: > >There seems to be a trend nowadays to use the phrase "expert systems" to >mean rule-based systems, not to mean any systems that mimick expert >behavior. While I'm not sure I like the terminology, I think that it's >beneficial to have a seperate catagory for rule-based-systems work, >since that's often very different from other A.I. work .... I'm inclined to agree. Once upon a time, "Knowledge Based System" equalled "Expert System" equalled "Rule Based System", none of which equalled "AI System". AI sympathists looked askance at the sudden mushrooming of expert systems with suspicion and cynicism as a band- wagon for squeezing as much cash as possible out of gullible sponsors. (And perhaps the old "if it's *that* easy to do, it can't be AI" attitudes came around again...) But KBS work is now returning to the stable, and concerning itself more and more with "real AI" (!) issues - use of metaknowledge for planning and control, problems of learning, ... so now when people say "expert system" they could mean a KBS or they could mean a "first generation" rule-based system. My guess is that KBS will replace ES as the preferred term for forthcoming systems, and that ES will shrink to denoting the things that you make using a commercially- available ES shell: typically, rule-based (and that don't mean much more than computer-based) systems. As for the other question of whether an ES should explain itself: it's fairly easy to make a RBS give some kind of explanation, and so it's been done frequently. The domain and user context might not require it, and the nature of the explanation might be useless anyway, but .... I'd go along with the other correspondents who argue that a KBS might just not have access any more (at the time you asked for it) to the 'exact' reasons for its outputs and that maybe there is no 'exact' reason if there is indeterminacy/context-dependency built in. Generally, the ability to give explanation on demand seems to be only an optional, useage-dependent, external characteristic rather than an essential universal internal one. Vic Churchill ( ...!mcvax!ukc!stl!jvc +44-279-29531 x 2546) STL Ltd., London Road, Harlow, Essex CM17 9NA, U.K. ------------------------------ Date: Fri, 13 Mar 87 09:53:51 MST From: Roy Masrani Subject: reply to dear abby Dear abby (sigh). And I thought you had all the answers! Just to summarize the responses (wow.. so many of them too!) 1. justification mechanisms are not good enough yet, ergo expert systems do not need a justification capability. This is missing the point. Just because current justification mechanisms (jms) simply print a trace of its reasoning is not an argument against the utility of jms per se. perhaps the work on "deep model" reasoning will come up with good jms. >When they ask for "the reason why" should I have written >a huge explanation database instead of relying on the >programming language internal logic control??????? (Michaelson) No, but *when* they ask why, you should get the (current state of the art) explanation module that was keeping track of the reasoning system to spit out what it has. Pretty difficult to do in prolog unless you build some kind of es shell on top of it. 1b. Humans do not backtrack over a line of reasoning. Humans dont justify themselves. An interesting comment by B. Nevin. >....Instead, we reconstruct what such a line of reasoning > might plausibly be. It's called rationalization. To me, a doctor who says "S**t, I prescribed x... better cover myself" is one who is rationalizing his/her decisions. (but at least s/he is providing a justification for the decision (:->)) Even if the expert is reconstructing the reasoning, it is based on the knowledge of the field, and it is difficult (for me) to argue that the "rationalization" wasn't a trace of the line of reasoning since you dont have access to the reasoning in the first place. I dont ask my doctor to always explain herself, but if she was not able to when i did, i would leave pretty quickly. 2. the term "expert system" is not well defined. I couldn't agree more with this more. Three terms are often used interchangeably "expert system, rule-based system, knowledge-based system". A program that behaves as an expert (i.e. makes expert-like decisions) cannot be considered an expert system. Is SPSS (the statistical package written in fortran) an expert system.. it sure performs functions similar to an expert statistician (relative to me, anyway). A program that only has a clear knowledge/control separation cannot be called an es. any system written on top of a spreadsheet has a clear knowledge/control separation. >Knowledge-based system technology is a programming methodology, which >facilitates the incorporation of "human or expert" knowledge. Hence, the >criterion that explanation facilitiy is a must for a knowledge based >system (or an expert system once you add the expert's knowledge) is >to be questioned. [...users don't like rule printouts, they like >"a more robust ENGLISH translation and "nice graphics" (Sriram) I dont see how your (pretty broad) definition of a knowledge-based system negates the need for an explanation facility (if kb-system in your reality == expert system). The second comment simply supports my view (cf 1) >...it seems to me that disputes over whether explanation is "needed" >before you can call it an expert system are missing the point... (Coffee) Wish I had said that. 3. depends on what the es will be used for. es will be more accepted if they have an explanation facility. I guess when i think of expert systems' use, i usually think in terms of it being used as a consultant or advisor (cf "our expert is overworked, and getting old" stories). Using an "expert system" in "production" seems analogous to human experts writing a set of instructions for use when they are not available. Would consulting the set of instructions constitute a session with the expert? Putting a justification mechanism if/when needed is another way of saying that the facility is a "luxury" and not really necessary. I think that perhaps I have a very tight view of the term "expert system" and its use. Thanks for the feedback, roy ------------------------------ End of AIList Digest ******************** From in%@vtcs1 Mon Mar 16 02:35:33 1987 Date: Mon, 16 Mar 87 02:35:25 est From: vtcs1::in% To: ailist@sri-stripe.arpa Subject: AIList Digest V5 #79 Status: R AIList Digest Sunday, 15 Mar 1987 Volume 5 : Issue 79 Today's Topics: Philosophy - Consciousness, Review - Eliza/Parry/Ractor, Humor - Humor Interface Project ---------------------------------------------------------------------- Date: 9 Mar 87 09:23:00 EST From: "WHITE::PSOTKA" Reply-to: "WHITE::PSOTKA" Subject: RE: AIList Digest V5 #71 Consciousness and memory appear to be connected: but what is the connection? Davis in a posting on March 7, 1987 offers the opinion that consciousness allows us to be good psychologists; to understand other humans in ways that a Turing machine could not. It seems an interesting suggestion. If consicousness is tied into memory, it is to personalize the memory and make it distinguishable from external events; the environment; the reality that exists continuously outside and that we use so intensively to support our mental apparatus. The external world helps us to think in so many ways; cues for arithmetic in supermarkets; support for troubleshooting complex equipment (What would we do if we could not see the instruments?); questions raised implicitly by mystifying situations, etc. etc. How can we tell what is our own input (memory) from what comes naturally: we are "conscious" of the real world and this consciousness becomes part of the record of the world. So consciousness is functional; we could not separate our memories from outside reality without it. At least, that appeasrs to be an interesting clue to add to the puzzle. ------------------------------ Date: Tue, 10 Mar 87 08:03 EST From: Seth Steinberg Subject: Historical Perspective on the Consciousness Debate I couldn't help noticing that this debate has its antecedants: "Whatever does this, reasons: and if a machine produces the effects of reason, I see no more ground for denying it the reasoning power, because it is unconscious, than I see for refusing Mr. Babbage's engine the title of a calculating machine on the same grounds." >From T.H. Huxley's 1871 essay Mr. Darwin's Critics - discussing whether a hunting dog reasons. While this essay is largely concerned with the origins of the species, it examines the arguments for the necessity of the special creation of human consciousness (one of Wallace's key reservations). Examining some of the anti-evolutionary arguments shows just how shocking Freud's emphasis on the subconscious would be. Seth ------------------------------ Date: Tue, 10 Mar 87 11:31 CDT From: "Alan McDonley M/S 3719 (303) 593-5356" Subject: Minds are a terrible thing to explain While contemplating about methods of measuring conciousness, I was asked a *WHO* question. Before I could say the name of the person as an answer, another thought stream began. I knew the name of the person, I knew which person I was thinking of, but for some reason I could not say or bring to *mind* the name of the person. In fact the recognition of the inability to recall the words flooded my thoughts. I contemplated on the subject of inferences rapidly happening but not yet creating the path to the name in my memory. I wondered if I should stop *worrying* about remembering so that more processing resources would be available to connect to the name I was attempting to retrieve, when the name burst into my thoughts. Now after reading the AILIST for some time, I am humbled to have had what some have called first and second order conciousness experiences and wonder if there are separate processors for each level or are thoughts the postings of time sliced knowledge sources on some blackboard? Ps. Since Clyde is an elephant, Clyde is a Republican. ------------------------------ Date: 12 Mar 87 15:07:15 GMT From: mcvax!ukc!its63b!dougie@seismo.css.gov (D Nisbet) Subject: Eliza/Parry - A summary I have had a fair response concerning my Ractor/eliza query. Here follows a summary of the e-mail I received. Thanks to all who replied. From: "BARNETTE,JAMES RICHARD JR" Message-Id: <8703051751.AA00500@gitpyr.gatech.edu> Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ... Organization: Georgia Institute of Technology "The Policeman's Beard is Half-Constructed" is published by Warner Brothers. When I bought it it was about eleven dollars. The author of the book is Racter, a program which writes English prose. The program itself is by William Chamberlain (he also wrote the introduction.) There was an article a few years ago in Scientific American describing Racter. It was in the regular feature "Computer Recreations" by A.K. Dewdney. Sorry, but I don't remember more. The book is really just a collection of various short writings: short (two paragraph) essays, free verse poetry (which might be called structured prose), and even two pages of (horribly bad) limericks. There is also one short story, "Soft Ions", which was originally published in Omni magazine. (Sorry, no idea of what issue). The book is very interesting; I would recommend it if you want to see what kind of prose computers can write. Although Racter writes grammatically correct English, the meaning of his (its?) writing is usually quite bizarre. For instance, in one of the first short essays of the book, an essay on love, Racter asks "...does steak love lettuce?". Racter is good enough that his writing might be mistaken for a human's, but a psychiatrist would probably diagnose him as very psychotic. Richard Barnette Georgia Tech P.O. Box 35951 Atlanta, GA 30332 USA -- BARNETTE,JAMES RICHARD JR Georgia Insitute of Technology, Atlanta Georgia, 30332 uucp: ...!{akgua,allegra,amd,hplabs,ihnp4,seismo,ut-ngp}!gatech!gitpyr!gt5951b ARPA: gt5951b@pyr.ocs.gatech.edu ==================== >From copp@bellcore.UUCP Mon Mar 9 16:43:10 GMT 1987 From: copp@bellcore.UUCP (David H. Copp) Subject: Re: Eliza, Doctor, Parry, Ractor, etc, ... Message-ID: <231@bellcore.UUCP> Reply-To: copp@bellcore.UUCP (David H. Copp) Organization: Bell Communications Research Keywords: Eliza, Ractor, Parry, Doctor, software, literature. "The Policeman's Beard is Half Contructed," authored by Racter (with a little help from William Chamberlain), Warner Books Inc., 666 Fifth Avenue, New York, NY 10103, USA. First printing Oct 1984. This is a new publisher. You may have to write directly to Warner Books, P.O. Box 690, New York, NY 10019, USA. $0.75 per order and $0.50 per copy. This is not a technical book. It tells you very little about Racter. It is an amusing addition to your coffee table. Martin Gardner (or was it Hofstedder?) devoted two or three pages to Racter about three years ago (Scientific American). Good article. The program itself can be purchased, IBM PC format, for about $75--see the SA article.) -- David H. Copp (201) 829-4337 bellcore!copp ================= Subject: police mans beard is half constucted The policemans beard is half constructed was written by Ractor. Its pres ently being released on micros by Hayden i belive. Ive seen it for the mac and i bm pc. it an excelent program. S.David Streiff Univ of Hartford W Hartford CT BitNet: STREIFF@HARTFORD.BITNET ==================== From: Robert Farrell Subject: Eliza I have a small but interesting Eliza that I wrote in T (a dialect of Scheme). I could put it in the public domain if you want it. It emulates a car mechanic and is a lot of fun. It would be easy to add more rules or convert it to another lisp, since it is written clearly and is pretty well documented. Why do you want an Eliza - just for fun or for something you are doing (e.g. teaching pattern-matching)? I have included a transcript and a few notes about the program below. Just send me a note and I will give you the whole program ... it is only about 700 lines long. If you don't have some sort of LISP to convert it to, or don't want to do any work converting the program, then this isn't the Eliza for you. E E D D --> "Rob calling" C C G--G Farrell@YALE.ARPA *** decvax!yale!Farrell.UUCP *** BITNET: Farrell@yalecs.BITNET ==================== From: Chris Price Subject: Re: Eliza... Eliza should be easily available at Edinburgh. I can think of two places where it is free: 1) In Poplog as a library, you do pop11 -eliza 2) In GNU emacs - a free version of emacs widely distributed. Cheers, Chris Price. ======================= From: Mike Urban Organization: TRW Inc., Redondo Beach, CA In article <310@its63b.ed.ac.uk> you write: > >I have heard about the various "chatty" programs which have been written >to imitate Psychiatrists (sp?), Doctors, Scribe's, etc, but have never >had the opportunity to play (play?!) use any of these programs. This kind >of software interests me a lot and would like to know if any of them >(or similar type) are freely available. > >There is a book, I believe, titled "The Policeman's Beard is >Half-Constructed" which chronicles the 'works' of one of these >programs (I can't remember which). I have ported a version of "DOCTOR" (a.k.a. Eliza) to run with David Betz's Xlisp 1.6. Xlisp is a public-domain version of LISP and has been posted to the net in its Unix incarnation. My version includes an Esperanto translation of DOCTOR's "script", intended to provide language practice. "The Policeman's Beard" is based on Racter. I don't know about its availability. -- Dougie Nisbet University of Edinburgh | ...seismo!mcvax!ukc!its63b!dougie Medical Statistics Unit | dougie@uk.ac.ed.its63b Medical School Teviot Place Edinburgh Scotland ------------------------------ Date: Thu, 12 Mar 87 16:01:37 CST From: Will Hill Subject: Humor Interface Project For the AIlist. Remember the Viet Cong? Well, I'll get back to them in a minute. This memo announces the formation of a new project, the Humor Interface Project, sometimes known in revolutionary circles as the Interface-esE liberation Army, or, IEA, (pronounced at the top of your lungs, as EYEEE-EEEEE-AHHHHH... while drumming your chest). The members seek no official status whatsoever and will accept none when they succeed. I am not a member of this group but have been retained by them as their publicist for an indecent sum of money. They have requested that I set before the public their noble raisin d'etre [sic], their altruistic intentions, their anti-establishment methods, and of course, their consulting fee scale and answering service number. This project formed at a recent conference during the "HCI and All Possible Universes" session. Or was it the "HCI and All Possible Universes Containing Alcohol" session? Anyway, the group intends to implement, study, reflect and publish about humorous interface techniques. The idea started with the question, "Suppose we tried to make a computer act like Robin Williams or Jonathan Winters? Not staged humor, not joke telling, not static cartoons but interactive... contextual humor, adlibbing on material provided by the combination of user and system programmer?" From there things went straight down or straight up depending upon your perspective. The group shared their favorites. Windows that crack or melt into a slag heap. The MacIntosh IBM DOS emulator that, when fired up, begins to put up a zippy MacIntosh screen, stops halfway down the screen to declare, "Oops? Sorry. You wanted 195Os technology." It then goes into command line mode. The supposed unused ROM hook in the Mac that would have caused a monkey to dance across the screen ONCE upon the 7698th (or whatever) boot of the machine. Insects crawling around the screen. As you read this, project programmers in ski-masks are already coding up: ELUSIVE MENU: When the mouse cursor enters such menus, the menus dodge away while insulting the user with appropriate language and gestures. Somebody informed us, this is just like the Mac Bomb program. CRASHING WINDOWS: You begin to move a window. Suddenly it accelerates out of your control up toward the corner of the screen. When it reaches the corner, it smashes to pieces, falling to the bottom of the screen. Appropriate sounds effects are heard. Email is sent to the site manager blaming you for the broken window. AEROBIC WINDOWS: You begin to move a window and suddenly it accelerates out of your control bouncing around the screen faster and faster. It finally slows down an sits on your screen off in the direction you were moving it, but huffing and puffing, sort of expanding in and out. You begin working again, it's breathing slows and stops after a few moments. FONTS: that scream, melt, sigh or beg as you delete them. Giggle as you transpose characters. Yawn when you come back to them in the morning. Burp when you edit them after lunch. PEOPLE INSIDE THE MONITOR: You get an error. A large face leans in from the left, gives you a "Lettermanesque look", like he's got a horrible flavor on his tongue, and then leans back out of the monitor. ENCRYPTION WAVES undulate through your current text buffer occasionally stopping at your cursor to make stupid demands. They go away for a while when you give in. GIGANTIC SCREEN-FILLING BODY PART MOUSE CURSOR ICONS: You can move them no more than a half inch in each direction. Need the Interface-esE liberation Army say more? The group suspects that a lot could learned about the un-obvious communication possibilities of computational media by analyzing successful and failed humor attempts. At least unspoken expectations of interface experience should stand out in bold relief as humor violates them. Misunderstandings of those same expectations and experiences should stand out as humor fails. Back to the Viet Cong. Remember that a large percentage of the South Vietnamese Government was V.C.? Its the same way with the Humorous Interface Project. You're part of it. We're collecting examples of humorous interface techniques. They might be implemented or not If you know of some, please send them along to will@mcc.com . We'd much appreciate it. At sometime, somehow, we'll publish the best of what you send in back out into the community. Send code if you like. I'll end with a quote from the HIP group. "The project is putting together a macro, With-Humorous-Interface. Dare you run inside it? Who knows what you'll see and hear next time you cycle through text called back from the kill ring. Text YOU killed." will@mcc.com publicist for The Humor Interface Project, Alias "Humor In Your Face", "Humid Interface" And "Interface-Ese liberation Army (EYEEE-EEE-AHHH...) ------------------------------ End of AIList Digest ********************