Minds and Machines 2 (3):267-282 (1992)
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Abstract |
In this paper we attempt to develop a problem representation technique which enables the decomposition of a problem into subproblems such that their solution in sequence constitutes a strategy for solving the problem. An important issue here is that the subproblems generated should be easier than the main problem. We propose to represent a set of problem states by a statement which is true for all the members of the set. A statement itself is just a set of atomic statements which are binary predicates on state variables. Then, the statement representing the set of goal states can be partitioned into its subsets each of which becomes a subgoal of the resulting strategy. The techniques involved in partitioning a goal into its subgoals are presented with examples
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Keywords | Problem-solving strategy problem representation refinement machine learning mechanical discovery |
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DOI | 10.1007/BF02454223 |
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References found in this work BETA
Learning Problem Solving Strategies Using Refinement and Macro Generation.H. Altay Güvenir & George W. Ernst - 1990 - Artificial Intelligence 44 (1-2):209-243.
Search and Reasoning in Problem Solving.Herbert A. Simon - 1983 - Artificial Intelligence 21 (1-2):7-29.
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