Date: Wed 19 Oct 1988 20:26-EDT From: AIList Moderator Nick Papadakis Reply-To: AIList@AI.AI.MIT.EDU Us-Mail: MIT LCS, 545 Tech Square, Rm# NE43-504, Cambridge MA 02139 Phone: (617) 253-6524 Subject: AIList Digest V8 #107 To: AIList@AI.AI.MIT.EDU Status: RO AIList Digest Thursday, 20 Oct 1988 Volume 8 : Issue 107 Seminars: The SB-ONE Knowledge Representation Workbench - Alfred Kobsa Cooperative Problem Solving Systems - Gerhard Fischer Machiavelli : A Polymorphic Lang. for oo db - Atsushi Ohori The Computational Linguistics of DNA - David Searls OSCAR: A General Theory of Rationality - John Pollock What My Robot Should Do Next - Ian Horswill Expert Systems in Predictive Toxicology - Arnott and Snow Church's Thesis, Connectionism, and Cognitive Science - Raymond J. Nelson ---------------------------------------------------------------------- Date: Tue, 27 Sep 88 11:21:08 EDT From: finin@PRC.Unisys.COM Subject: The SB-ONE Knowledge Representation Workbench - Alfred Kobsa AI SEMINAR UNISYS PAOLI RESEARCH CENTER The SB-ONE Knowledge Representation Workbench Alfred Kobsa International Computer Science Institute, Berkeley (on leave from the University of Saarbruecken, West Germany) The SB-ONE system is an integrated knowledge representation workbench for conceptual knowledge which was specifically designed to meet the requirements of the field of natural-language processing. The representational formalism underlying the system is comparable to KL-ONE, altough different in many respects. A Tarskian semantics is given for the non-default part of it. The user interface allows for a fully graphical definition of SB-ONE knowledge bases. A consistency maintenance system checks for the syntactical well-formedness of knowledge definitions. It rejects inconsistent entries, but tolerates and records incomplete definitions. A partition mechanism allows for the parallel processing of several knowledge bases, and for the inheritance of (incomplete) knowledge structures between parititons. The SB-ONE system is being employed in XTRA, a natural-language access system to expert systems. The use of SB-ONE for meaning representation, user modeling, and access to the expert system's frame knowledge base will be briefly described. 10:00am Friday, October 14 BIC Conference Room Unisys Paoli Research Center Route 252 and Central Ave. Paoli PA 19311 -- non-Unisys visitors who are interested in attending should -- -- send email to finin@prc.unisys.com or call 215-648-7446 -- * COMING ATTRACTION: On October 19, Marilyn Arnott (PhD from Texas in * * Chemistry) will speak on the topic of an expert system for predictive * * toxicology. The seminar will be held at 2:00 PM in the BIC Conference * * Room. An exact title and an abstract will be distributed when they * * become available. * ------------------------------ Date: Wed, 12 Oct 88 14:32:30 edt From: dlm@allegra.att.com Subject: Cooperative Problem Solving Systems - Gerhard Fischer Cooperative Problem Solving Systems Gerhard Fischer University of Colorado October 13, 1988 AT&T Bell Labs -- Murray Hill 3D-436 -- 10:00 am ABSTRACT Over the last few years we have constructed a number of intelligent support systems (e.g. documentation systems, help systems, critics, and a "software oscilloscope") which support limited cooperative problem solving processes. These systems and their limitations will be discussed and future research directions towards the goal of truly cooperative problem solving systems will be presented. Sponsor: R.J.Brachman ------------------------------ Date: Sun, 16 Oct 88 14:46:30 EDT From: finin@PRC.Unisys.COM Subject: Machiavelli : A Polymorphic Lang. for oo db - Atsushi Ohori AI SEMINAR UNISYS PAOLI RESEARCH CENTER Atsushi Ohori University of Pennsylvania Machiavelli : A Polymorphic Language for Object-oriented Databases Machiavelli is a programming language for databases and object-oriented programming with a strong, statically checked type system. It is an extension of the programming language ML with generalized relational algebra, type inheritance and general recursive types. In Machiavelli, various database operations including join and projection are available as polymorphic operations, ML's abstract data types are extended with inheritance declarations, and the type system includes general recursive types. In this talk, I will first introduce Machiavelli and show examples demonstrating its expressive power in the context of both database programming and object-oriented programming. I will then describe the theoretical aspects of the language. For the theoretical aspects of the language, I will show that, by defining syntactic orderings on subsets of terms and types that correspond to database objects, a generalized relational algebra can be introduced in a strongly typed functional programming language. By allowing conditions on substitutions for type variables, Milner's type inference algorithm can be also extended to those new constructs. I will then show that by using the type inference mechanism, ML's abstract data types can be extended to support inheritance. Finally I will describe how the above mechanisms can be extended to recursive types. Joint work with Peter Buneman. 10:30 am - November 2, 1988 BIC Conference Room Unisys Paoli Research Center Route 252 and Central Ave. Paoli PA 19311 -- non-Unisys visitors who are interested in attending should -- -- send email to finin@prc.unisys.com or call 215-648-7446 -- ------------------------------ Date: Tue, 18 Oct 88 08:40:47 EDT From: finin@PRC.Unisys.COM Subject: The Computational Linguistics of DNA - David Searls UNIVERSITY OF PENNSYLVANIA DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE The Computational Linguistics of DNA David Searls Unisys Paoli Research Center Genetic information, as expressed in the four-letter alphabet of the DNA of living organisms, represents a complex and richly-expressive linguistic system that encodes procedural instructions on how to create and maintain life. There is a wealth of understanding of the semantics of this language from the field of molecular biology, but its syntax has been elaborated primarily at the lowest lexical levels, without benefit of formal computational approaches that might help to organize its description and analysis. In this talk, I will examine some linguistic properties of DNA, and propose that generative grammars can and should be used to describe genetic information in a declarative, hierarchical manner. Furthermore, I show how a Definite Clause Grammar implementation can be used to perform various kinds of analyses of sequence information by parsing DNA. This approach promises to be useful in recombinant DNA experiment planning systems, in simulation of genetic systems, in the interactive investigation of complex control sequences, and in large-scale search over huge DNA sequence databases. THURSDAY, OCTOBER 20, 1988 REFRESHMENTS 2:30 - 3:00 129 Pender COLLOQUIUM 3:00 - 4:30 216 MOORE ------------------------------ Date: 18 Oct 88 15:18:18 GMT From: sunybcs!rapaport@rutgers.edu (William J. Rapaport) Subject: OSCAR: A General Theory of Rationality - John Pollock =============================================================================== UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE UPDATE =============================================================================== UNIVERSITY AT BUFFALO STATE UNIVERSITY OF NEW YORK DEPARTMENT OF PHILOSOPHY GRADUATE GROUP IN COGNITIVE SCIENCE and GRADUATE RESEARCH INITIATIVE IN COGNITIVE AND LINGUISTIC SCIENCES PRESENT JOHN POLLOCK Department of Philosophy University of Arizona OSCAR: A General Theory of Rationality The enterprise is the construction of a general theory of rationality and its implementation in an automated reasoning system named OSCAR. The paper describes a general architecture for rational thought. This includes both theoretical reasoning and practical reasoning, and builds in important interconnections between them. It is urged that a sophis- ticated reasoner must be an _introspective reasoner_, capable of moni- toring its own reasoning and reasoning about it. An introspective rea- soner is built on top of a non-introspective reasoner that represents the system's default reasoning strategies. The introspective reasoner engages in practical reasoning about reasoning in order to overide these default strategies. The paper concludes with a discussion of some aspects of the default reasoner, including the manner in which reasoning is interest-driven and the structure of defeasible reasoning. Wednesday, October 26, 1988 4:00 P.M. 684 Baldy Hall, Amherst Campus There will be an evening discussion at 8:00 P.M., at Mary Galbraith's, 130 Jewett Parkway, Buffalo. Copies of the paper are available from Bill Rapaport, Dept. of Computer Science, 636-3193. Contact Rapaport or Jim Lawler, Dept. of Philosophy, 636-2444, for further information. ------------------------------ Date: Tue 18 Oct 88 12:24:18-EDT From: Marc Vilain Subject: What My Robot Should Do Next - Ian Horswill BBN Science Development Program AI Seminar Series Lecture WHAT MY ROBOT SHOULD DO NEXT: NAVIGATION WITHOUT PLANNING; VISION WITHOUT INVERSE-OPTICS. Ian D. Horswill MIT Artificial Intelligence Lab (IDH@WHEATIES.AI.MIT.EDU) BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Tuesday October 25 In this talk I will discuss a system which performs a variety of low-level navigation activities without many of the traditional trappings of robot navigation such as mapping, planning, callibrated cameras, surface reconstruction, or dead reconning. In particular, the system chases moving objects, investigates static ones, and follows along corridors using a camera for visual feedback. Rather than committing to a pre-planned path and attempting to follow it accurately, the system constantly re-answers the question "what should I do next?". By continuously reasessing the situation, the system is able to operate in dynamic and even unpredictable environments where mapping and planning are unfeasible. By breaking the problem up into managable routine tasks such as corridor following, the system is able to perform the tasks using dramatically simpler machinery than conventional systems while guaranteeing bounded response time (0.2 seconds in our present implementation). ------------------------------ Date: Tue, 18 Oct 88 14:32:32 EDT From: finin@PRC.Unisys.COM Subject: Expert Systems in Predictive Toxicology - Arnott and Snow AI SEMINAR UNISYS PAOLI RESEARCH CENTER EXPERT SYSTEMS IN PREDICTIVE TOXICOLOGY Marilyn S. Arnott and Ina B. Snow LogiChem Inc. Boyertown, PA 19512 A prototype system focusing on the possible teratogenicity of members of one class of chemicals, aliphatic acids, has been developed and validated. The system evaluates any chemical which can be metabolized to an aliphatic acid, then performs structure-activity relationship (SAR) analysis on the resulting acid to determine its potential teratogenicity. The prototype was validated by comparing results from the system to laboratory results from three types of teratogenesis bioassays on 36 aliphatic acids. The outcome cast doubt on the usefulness of one of the bioassays, and, additionally, detected an error in the published structure of one of the compounds tested. We are presently in the early design phase of an expert system to predict carcinogenic potential of chemicals. The system is being developed in cooperation with senior scientists at the EPA, who use SAR analysis to evaluate the potential health hazards of new chemicals under review by the agency. Wednesday, October 19, 2:00 BIC Conference Room Unisys Paoli Research Center Paoli Pa -- non-Unisys visitors who are interested in attending should -- -- send email to finin@prc.unisys.com or call 215-648-7446 -- ------------------------------ Date: Wed, 19 Oct 88 16:53:17 EDT From: rapaport@cs.Buffalo.EDU (William J. Rapaport) Subject: Church's Thesis, Connectionism, and Cognitive Science - Raymond J. Nelson UNIVERSITY AT BUFFALO STATE UNIVERSITY OF NEW YORK BUFFALO LOGIC COLLOQUIUM GRADUATE GROUP IN COGNITIVE SCIENCE and GRADUATE RESEARCH INITIATIVE IN COGNITIVE AND LINGUISTIC SCIENCES PRESENT RAYMOND J. NELSON Truman Handy Professor of Philosophy Case Western Reserve University CHURCH'S THESIS, CONNECTIONISM, AND COGNITIVE SCIENCE Wednesday, November 16, 1988 4:00 P.M. 684 Baldy Hall, Amherst Campus The Church-Turing Thesis (CT) is a central principle of contemporary logic and computability theory as well as of cognitive science (which includes philosophy of mind). As a mathematical principle, CT states that any effectively computable function of non-negative integers is general recursive; in computer and cognitive-science terms, it states that any effectively algorithmic symbolic processing is Turing comput- able, i.e., can be carried out by an idealized stored-program digital computer (one with infinite memory that never fails or makes mistakes). In this form, CT is essentially an empirical principle. Many cognitive scientists have adopted the working hypothesis that the mind/brain (as a cognitive organ) is some sort of algorithmic symbol- processor. By CT, it follows that the mind/brain is (or realizes) a system of recursive rules. This may be interpreted in two ways, depend- ing on two types of algorithm, free or embodied. A free algorithm is represented by any program; an embodied algorithm is one built into a network (such as an ALU unit or a neuronal group). CT is being challenged by connectionism, which asserts that many cogni- tive processes, including perception in particular, are not symbol processes, but rather subsymbol processes of entities that have no literal semantic interpretation. These are parallel, distributed, asso- ciative memory processes totally unlike serial, executive-driven, von Neumann computers. CT is also being challenged by evolutionism, which is a form of connectionism that denies that phylogenesis produces a mind/brain adapted to fixed categories or distal stimuli (even fuzzy ones). Computers deal only with fixed categories (either in machine language, codes such as ASCII, or declarations in higher-level languages). So, if connectionists are right, CT is false: there are processes that are provably (I will suggest a proof) effective and algo- rithmic but are not Turing-computable. However, if CT in empirical form is true, and if the processes involved are effective, then connectionism or, in general, anti-computationalism is false. A direct argument that does not appeal to CT but that tends to confirm it is that embodied algorithm networks as a matter of fact are parallel, distributed, associative, and subsymbolic even in von Neumann computers, not to say super-multiprocessors. Finally, I claim that the embodied algorithm network models are not only _not_ antithetical to evolutionism but dovetail nicely with the theory that the mind/brain evolves through the life of the individual. REFERENCES Edelman, G. (1987), _Neural Darwinism_ (Basic Books). Nelson R. J. (1988), ``Connections among Connections,'' _Behavioral & Brain Sci._ 11. Smolensky, P. (1988), ``On the Proper Treatment of Connectionism,'' _Behavioral & Brain Sci._ 11. There will be an evening discussion at a time and place to be announced. Contact John Corcoran, Department of Philosophy, 636-2444 for further information. ------------------------------ End of AIList Digest ********************