Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Path: utzoo!mnetor!uunet!husc6!rutgers!bellcore!faline!ulysses!ucbvax!VENICE.AI.SRI.COM!lansky From: lansky@VENICE.AI.SRI.COM (Amy Lansky) Newsgroups: comp.ai.digest Subject: Seminar - Hypothetical Reasoning (SRI) Message-ID: <8710300055.AA18619@venice> Date: Thu, 29-Oct-87 19:55:04 EST Article-I.D.: venice.8710300055.AA18619 Posted: Thu Oct 29 19:55:04 1987 Date-Received: Sun, 8-Nov-87 11:42:33 EST Sender: daemon@ucbvax.BERKELEY.EDU Organization: The ARPA Internet Lines: 28 Approved: ailist@kl.sri.com DEFAULTS AND CONJECTURES: HYPOTHETICAL REASONING FOR EXPLANATION AND PREDICTION David Poole (dlpoole%watdragon.waterloo.edu@relay.cs.net) Logic Programming and Artificial Intelligence Group University of Waterloo 11:00 AM, MONDAY, November 2 SRI International, Building E, Room EJ228 Classical logic has been criticised as a language for common sense reasoning as it is monotonic. In this talk I wish to argue that the problem is not with logic, but with how logic is used. An alternate way to use logic is by using theory formation; logic tells us what a theory implies, an inconsistency means that the theory cannot be true of the world. I show how the simplest form of theory formation, namely where the user supplies the possible hypotheses, can be used as a basis for default reasoning and model-based diagnosis. This is the basis of the "Theorist" system being built at the University of Waterloo. I will discuss what we have learned from building and using our system. I will also discuss distinctions which we have found to be important in practice, such as between explaining observations and making predictions; and between normality conditions (defaults) and abnormality conditions (prototypes, conjectures, diseases). The effects of these distinctions on recognition and prediction problems will be presented along with algorithms, theorems and examples.