Learning problem solving strategies using refinement and macro generation

Date
1990
Authors
Güvenir, H. A.
Ernst, G. W.
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Source Title
Artificial Intelligence
Print ISSN
0004-3702
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Publisher
Elsevier BV
Volume
44
Issue
1-2
Pages
209 - 243
Language
English
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Abstract

In this paper we propose a technique for learning efficient strategies for solving a certain class of problems. The method, RWM, makes use of two separate methods, namely, refinement and macro generation. The former is a method for partitioning a given problem into a sequence of easier subproblems. The latter is for efficiently learning composite moves which are useful in solving the problem. These methods and a system that incorporates them are described in detail. The kind of strategies learned by RWM are based on the GPS problem solving method. Examples of strategies learned for different types of problems are given. RWM has learned good strategies for some problems which are difficult by human standards. © 1990.

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Published Version (Please cite this version)