IRList Digest Sunday, 24 July 1988 Volume 4 : Issue 41 Today's Topics: Announcement - Chemical Information conf., email addresses? Call for Papers - 2nd Conference on AI & Law COGSCI - Connectionist Representations and Linguistic Inference - Michael Lesk on "Does Technology Affect How People Read?" - Model-Based Diagnostic Reasoning using Past Experiences News addresses are Internet or CSNET: fox@vtopus.cs.vt.edu or fox@fox.cs.vt.edu BITNET: foxea@vtvax3.bitnet (soon will be foxea@vtcc1) ---------------------------------------------------------------------- Date: Thu, 30 Jun 88 12:24:41 EDT From: David Johnson Subject: Chemical Information conference, mail addresses? Ed, ... The Sheffield address would be appreciated when you have the time, no rush. [Note: an earlier request was for email address of Peter Willett or any others at Sheffield; below is a request for address of P. Ingwersen. - Ed.] Would you have an ID for Peter Ingwersen? We have set our chemical information conference for the 3rd week in June 1990. We had to set a date and went on the assumption that SIGIR was usually about the 2nd week in June. We had other meetings that we wanted to not conflict with as well and there seemed less overlap with SIGIR (seems like just Peter Willett and me). We will be meeting at the Leeuwenhorst Conference Center in Noordwijkerhout, The Netherlands, so a Belgian venue for SIGIR could be very advantageous. ... Thanks for your help, David ------------------------------ Date: Fri, 15 Jul 88 13:27:51 EDT From: carole hafner Subject: Call for Papers - 2nd Conf. on AI and Law CALL FOR PAPERS Second International Conference on ARTIFICIAL INTELLIGENCE and LAW June 13-16, 1989 University of British Columbia Vancouver, British Columbia, Canada The field of AI and Law -- which seeks both to understand fundamental mechanisms of legal reasoning as well as to develop useful applications of AI to law -- is burgeoning with accomplishments in both basic research and practical applications. This increased activity is due in part to more widely available AI technology, advances in fundamental techniques in AI and increased interest in the law as an ideal domain for studying certain issues central to AI. The activities range from development of classic expert systems, intended as aids to lawyers and judges, to investigation of canonical elements of case-based and analogical reasoning. The study of AI and law both draws on and contributes to progress in basic concerns in AI, such as representation of common sense knowledge, example-based learning, explanation, and non-monotonic reasoning, and in jurisprudence, such as the nature of legal rules and the doctrine of precedent. The Second International Conference on Artificial Intelligence and Law (ICAIL-89) seeks to stimulate further collaboration between workers in both disciplines, provide a forum for sharing information at the cutting edge of research and applications, spur further research on fundamental problems in both the law and AI, and provide a continuing focus for the emerging AI and law community. Authors are invited to contribute papers on topics such as the following: -- Legal Expert Systems -- Conceptual Information Retrieval -- Case-Based Reasoning -- Analogical Reasoning -- Representation of Legal Knowledge -- Computational Models of Legal Reasoning In addition, papers on relevant theoretical issues in AI (e.g., concept acquisition, mixed paradigm systems using rules and cases) and in jurisprudence/legal philosophy (e.g., open-textured predicates, reasoning with precedents and rules) are also invited provided that the relationship to both AI and Law is clearly demonstrated. It is important that all authors identify the original contributions presented in their papers, exhibit understanding of relevant past work, discuss the limitations as well as the promise of their ideas, and demonstrate that the ideas have matured beyond the proposal stage. Each submission will be reviewed by at least three members of the Program Committee and judged as to its originality, quality, and significance. Authors should submit six (6) copies of an Extended Abstract, which must include a full list of references, by January 10, 1989 to the Program Chair: Edwina L. Rissland Department of Computer and Information Science University of Massachusetts, Amherst, MA 01003, USA; (413) 545-0332, rissland@cs.umass.edu. Submissions should be 6 to 8 pages in length, not including references. No electronic submissions can be accepted. Notification of acceptance or rejection will be sent out by early March. Final camera-ready copy of the complete paper (up to 15 pages) will be due by April 15, 1989. Program Chair: Edwina L. Rissland, University of Massachusetts/Amherst and Harvard Law School General Co-Chairs: Robert T. Franson, Joseph C. Smith, Faculty of Law, University of British Columbia Secretary-Treasurer: Carole D. Hafner, Northeastern University Program Kevin D. Ashley IBM Thomas J. Watson Reasearch Center Committee: Trevor J.M. Bench-Capon University of Liverpool Donald H. Berman Northeastern University Jon Bing University of Oslo Michael G. Dyer UCLA Anne v.d.L. Gardner Palo Alto, California L. Thorne McCarty Rutgers University Marek J. Sergot Imperial College London ------------------------------ Date: Fri, 6 May 1988 12:55 EDT From: Peter de Jong Subject: Cognitive Science Calendar [Extract - Ed.] Date: Friday, 29 April 1988 13:48-EDT From: reiter at harvard.harvard.edu (Ehud Reiter) Re: Harvard AI seminar Monday, May 9, 1988 4 PM Aiken 101 (Harvard University) (Tea at 3:45 pm, Aiken Main Lobby) Connectionist Representations and Linguistic Inference David S. Touretzky Computer Science Department Carnegie Mellon University DUCS is a neural network architecture for representing and manipulating frame-like structures. Slot names and slot fillers are diffuse patterns of activity spread over a collection of units. The choice of a distributed representation gives rise to certain useful properties not shared by conventional frame systems. One of these is the ability to retrieve a slot even if the slot name is not known precisely. Another is the ability to encode fine semantic distinctions as subtle variations on the canonical pattern for a slot. DUCS combines the flexiblity of parallel distributed processing with the structured flavor of conventional formalisms. but it is only suggestive of the sort of fluid knowledge representations connectionists are really after. In the second half of the talk I will discuss some current problems in connectionist natural language processing. Spreading activation/lateral inhibition architectures are insufficient to handle many interesting linguistic phenomena. For example, metonymy requires not only a rich knowledge representation, but also a flexible inference mechanism. Future connectionist models, employing more sophisticated network architectures, may provide solutions to these difficulties. ------------------------------ Date: Thu, 9 Jun 88 11:19:33 EDT From: Peter de Jong Subject: Cognitive Science Calendar [Extract - Ed.] Date: Tue, 7 Jun 88 17:04:44 edt From: Laureen Fletcher Subject: Talk by Michael Lesk "Does Technology Affect How People Read?" Lessons from the 18th Century. This is about reprinting the first edition of "Tristram Shandy;" duplicating 18th century fonts, etc. with some discussion of the switch from reading aloud to reading silently. "How to Tell a Pine Cone from an Ice Cream Cone -- Sense Disambiguation Using Machine Readable Dictionaries" Does a "fireman" feed fires or put them out? It depends on whether or not he is on a steam locomotive. This talk explains a scheme for deciding which sense of an ambiguous word is meant by counting overlaps of words in definitions in a machine-readable dictionary. Michael Lesk Division Manager of Computer Sciences Research Bell Communications Research Morristown, New Jersey Friday, June 10, 1988 2:00 - 3:00 p.m. E15-401 Host: Peg Schafer ------------------------------ Date: Fri, 10 Jun 88 16:53:11 EDT From: Peter de Jong Subject: Cognitive Science Calendar Date: Fri 10 Jun 88 13:52:39-EDT From: Marc Vilain Subject: BBN AI Seminar -- Phylis Koton BBN Science Development Program AI Seminar Series Lecture MODEL-BASED DIAGNOSTIC REASONING USING PAST EXPERIENCES Phylis Koton MIT Lab for Computer Science (ELAN@XX.LCS.MIT.EDU) BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Tuesday June 14 The problem-solving performance of most people improves with experience. The performance of most expert systems does not. People solve unfamiliar problems slowly, but recognize and quickly solve problems that are similar to those they have solved before. People also remember problems that they have solved, thereby improving their performance on similar problems in the future. This talk will describe a system, CASEY, that uses case-based reasoning to recall and remember problems it has seen before, and uses a causal model of its domain to justify re-using previous solutions and to solve unfamiliar problems. CASEY overcomes some of the major weaknesses of case-based reasoning through its use of a causal model of the domain. First, the model identifies the important features for matching, and this is done individually for each case. Second, CASEY can prove that a retrieved solution is applicable to the new case by analyzing its differences from the new case in the context of the model. CASEY overcomes the speed limitation of model-based reasoning by remembering a previous similar case and making small changes to its solution. It overcomes the inability of associational reasoning to deal with unanticipated problems by recognizing when it has not seen a similar problem before, and using model-based reasoning in those circumstances. The techniques developed for CASEY were implemented in the domain of medical diagnosis, and resulted in solutions identical to those derived by a model-based expert system for the same domain, but with an increase of several orders of magnitude in efficiency. Furthermore, the methods used by the system are domain-independent and should be applicable in other domains with models of a similar form. ------------------------------ END OF IRList Digest ********************