phyllis@utcsrgv.UUCP (Phyllis Eve Bregman) (01/16/84)
UofT Department of Computer Science Seminar Schedule for the week of January 16, 1984 Tuesday, January 17th, 3:00 P.M., GB244: Professor Larry Rendell Department of Computer Science, University of Guelph, Guelph, Ontario: "Efficient generalization learning in search". ABSTRACT: Generalization learning is inductive inference, acquisition of conceptual knowledge. It can be accomplished efficiently by structuring statistics obtained from observation of a given primary task. Such an approach has wide application in noisy environments. The probabilistic learning system (PLS) is currently being studied using the domain of search in state-space problems and games. Feature space clustering, knowledge accumulation, and regression have resulted in economical discovery of locally optimal evaluation functions. Adding an upper layer of (parallel) learning increases stability and power; adding lower layers may allow feature formation from elementary data (i.e. full inductive capability). Some unifying concepts and methods are suggested for efficient generalization learning. -- Phyllis Eve Bregman CSRG, Univ. of Toronto {decvax,linus,ihnp4,uw-beaver,allegra,utzoo}!utcsrgv!phyllis