Path: utzoo!utgpu!jarvis.csri.toronto.edu!neat.cs.toronto.edu!marina Newsgroups: ont.events From: marina@ai.toronto.edu (Marina Haloulos) Subject: Dr. Michael R. Lowry, Thursday 23 November 1989: ARTIFICIAL INTELLIGEN Message-ID: <89Nov13.144700est.2836@neat.cs.toronto.edu> Date: 13 Nov 89 19:47:29 GMT Department of Computer Science, University of Toronto (GB = Gailbraith Building, 35 St. George Street) ------------------------------------------------------------- ARTIFICIAL INTELLIGENCE SEMINAR GB119, at 11:00 a.m., Thursday 23 November 1989 Dr. Michael R. Lowry Kestrel Institute "Problem Reformulation through Abstraction, Design, then Implementation" The effectiveness of intelligent problem-solving systems is highly dependent on their representation of knowledge and formulation of problems. An intelligent system which automatically reformulates problems and changes representation is more effective at problem-solving than current AI systems which work within a fixed representation. This talk will present a theory of problem reformulation and a prototype reformulation system, STRATA, whose domain is algorithm synthesis. STRATA synthesizes algorithms in three steps. First it abstracts a problem by discovering problem properties and incorporating them into the domain theory. Second, it designs an abstract algorithm to solve the abstracted problem. Third, STRATA constructs an efficient implementation for the abstract algorithm. The end result of these three steps is a change of representation. This talk will emphasize an algebraic theory of problem abstraction. Abstraction is defined semantically on the problem domain rather than syntactically on the representation of the problem domain. This algebraic framework stresses both the abstraction of objects and the abstraction of operations in a problem domain. Problem abstraction is a specialized type of abstraction in which essential information is preserved while inessential information is thrown away. The semantic definition of problem abstraction is independent of representation system. This talk will describe how semantic abstraction can be realized as syntactic transformations of logical theories. A formal logic which is sound with respect to the semantics of abstraction has been developed. A method for calculating within this logic called Ontological Reasoning has been implemented. STRATA employs ontological reasoning to generate problem reformulations which represent problem abstractions. The mathematical foundation for this theory of problem reformulation is based on recent work in theoretical computer science, particularly abstract data types. This will be briefly described in the talk and is detailed in the thesis.