Path: utzoo!utgpu!water!watmath!clyde!att-cb!att-ih!pacbell!ames!pasteur!ucbvax!sunybcs.UUCP!nobody From: nobody@sunybcs.UUCP Newsgroups: comp.ai.digest Subject: Re: Software Wanted to Build a Mind Message-ID: <9574@sunybcs.UUCP> Date: 25 Mar 88 14:57:47 GMT References: <8803250637.AA22481@ucbvax.Berkeley.EDU> Sender: daemon@ucbvax.BERKELEY.EDU Reply-To: sunybcs!rapaport@rutgers.edu (William J. Rapaport) Organization: SUNY/Buffalo Computer Science Lines: 123 Approved: ailist@kl.sri.com In article <8803250637.AA22481@ucbvax.Berkeley.EDU> POPX@VAX.OXFORD.AC.UK writes: > SOFTWARE WANTED > - > TO BUILD A MIND You might be interested in the following document, excerpts of which follow; the full document is available by contacting us. William J. Rapaport Assistant Professor Dept. of Computer Science||internet: rapaport@cs.buffalo.edu SUNY Buffalo ||bitnet: rapaport@sunybcs.bitnet Buffalo, NY 14260 ||uucp: {ames,boulder,decvax,rutgers}!sunybcs!rapaport (716) 636-3193, 3180 || DEVELOPMENT OF A COMPUTATIONAL COGNITIVE AGENT Stuart C. Shapiro, Director William J. Rapaport, Associate Director SNePS Research Group Department of Computer Science SUNY at Buffalo 226 Bell Hall Buffalo, NY 14260 shapiro@cs.buffalo.edu, rapaport@cs.buffalo.edu OVERVIEW. The long term goal of the SNePS Research Group is to understand the nature of intelligent cognitive processes by developing and experiment- ing with a computational cognitive agent that will be able to use and understand natural language, and will be able to reason and solve prob- lems in a wide variety of domains. ... ACCOMPLISHMENTS. In pursuit of our long term goals, we have developed: (1) The SNePS Semantic Network Processing System, a knowledge- representation/reasoning system that allows one to design, imple- ment, and use specific knowledge representation constructs, and which easily supports nested beliefs, meta-knowledge, and meta- reasoning. (2) SNIP, the SNePS Inference Package, which interprets rules represented in SNePS, performing bi-directional inference, a mix- ture of forward chaining and backward chaining which focuses its attention on the topic at hand. SNIP can make use of universal, existential, and numerical quantifiers, and a specially-designed set of propositional connectives that include both true negation and negation-by-failure. (3) Path-Based Inference, a very general method of defining inheri- tance rules by specifying that the existence of an arc in a SNePS network may be inferred from the existence of a path of arcs specified by a sentence of a ``path language'' defined by a regu- lar grammar. Path-based reasoning is fully integrated into SNIP. (4) SNeBR, the SNePS Belief Revision system, based on SWM, the only extant, worked-out logic of assumption-based belief revision. (5) A Generalized Augmented Transition Network interpreter/compiler that allows the specification and use of a combined parsing- generation grammar, which can be used to parse a natural-language sentence into a SNePS network, generate a natural-language sen- tence from a SNePS network, and perform any needed reasoning along the way. (6) A theory of Fully Intensional Knowledge Representation, according to which we are developing knowledge representation constructs and grammars for the Computational Cognitive Mind. This theory also affects the development of successive versions of SNePS and SNIP. For instance, the insight we developed into the inten- sional nature of rule variables led us to design a restricted form of unification that cuts down on the search space generated by SNIP during reasoning. (7) CASSIE, the Computational Cognitive Mind we are developing and experimenting with, successive versions of which represent an integration of all our current work. CURRENT RESEARCH. Current projects being carried out by various members of the SNePS Research Group, some joint with other researchers, include: (1) VMES, the Versatile Maintenance Expert System: ... (2) Discussing and Using Plans: ... (3) Intelligent Multi-Media Interfaces: ... (4) Cognitive and Computer Systems for Understanding Narrative Text: ... (5) The Representation of Natural Category Systems and Their Role in Natural-Language Processing: ... (6) Belief Representation, Discourse Analysis, and Reference in Nar- rative: ... (7) Understanding Pictures with Captions: ... BIBLIOGRAPHY. A bibliography of over 90 published articles, technical reports, and technical notes may be obtained from Mrs. Lynda Spahr, at the address given above, or by electronic mail to spahr@gort.cs.buffalo.edu.