Steven.Minton@CAD.CS.CMU.EDU.UUCP (04/02/87)
Wei-Min Shen is giving this week's seminar. As usual, we will meet in 7220 at 3:15 on Friday. Here's the abstract: Analogical Transformation Extention and its Applications One of the aspects of learning by analogy is concerned with constructing and generalizing a transformation in the source domain and productively using it in the target domain. In this talk, we will discuss a preliminary approach, ATE, to the problem and its applications to: (1) creating new operators (more general than Macro-Operators) in AI discovery systems; and (2) solving problems in Geometric-Analogy Intelligence-Tests. For the first application, we will discuss in detail an implemented system, ARE. It starts with a small set of creative operations and a small set of heuristics, and uses ATE to create all the concepts attained by Lenat's AM system, and others as well. Besides showing a way to meet the criticisms of lack of parsimony that have been leveled against AM, the ARE system provides a route to discovery systems that are capable of "refreshing" themselves indefinitely by continually creating new operators. For the second application, we will compare the ATE approach with the method used by Evans in his program for solving problems in Geometric-Analogy Intelligence-Tests, and show that the ATE approach can solve the problems more efficiently. This discussion is a report on an ongoing project. We will appreciate any suggestions and comments. In case I cannot answer your hard questions, I will bring some delicious chinese rice pudding as my defence.