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Combining weak learning heuristics in general problem solvers

By T.L. McCluskey

Abstract

This paper is concerned with state space problem\ud solvers that achieve generality by learning strong\ud heuristics through experience in a particular domain. We specifically consider two ways of learning by analysing past solutions that can improve future problem solving: creating macros and the chunks. A method of learning search heuristics is specified which is related to 'chunking' but which complements the use\ud of macros within a goal directed system. An example of the creation and combined use of macros and chunks, taken from an implemented system, is described

Topics: Q1, T1
Year: 1987
OAI identifier: oai:eprints.hud.ac.uk:7938

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Citations

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