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Combining weak learning heuristics in general problem solvers

McCluskey, T.L. (1987) Combining weak learning heuristics in general problem solvers. In: 10th International Joint Conference on Artificial Intelligence, 1987, Milan, Italy.

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    Abstract

    This paper is concerned with state space problem
    solvers that achieve generality by learning strong
    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
    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.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: Q Science > Q Science (General)
    T Technology > T Technology (General)
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Pedagogical Research Group
    School of Computing and Engineering > Informatics Research Group
    School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces
    Related URLs:
    Depositing User: Sharon Beastall
    Date Deposited: 25 Jun 2010 08:46
    Last Modified: 16 Dec 2010 13:58
    URI: http://eprints.hud.ac.uk/id/eprint/7938

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