Generalized model for rational game tree search

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Decision-theoretic meta-reasoning is a well known scheme for controlling search that has been shown to be advantageous in numerous domains, including real-time planning and acting, and game-tree search. Although in numerous adversarial games, such as chess, brute-force search currently emerges as the best contender, there is still scope for planning in some situations. In order to take advantage of both schemes, we merge the planning and exhaustive search schemes through meta-reasoning. Approximate value of information is used to decide which of the types of computation operator to apply, and where. This is done by generalizing the Best Play for Imperfect Player (BPIP) search control model of [1] to allow for planning steps, as well as game-tree search steps. A rudimentary system employing these ideas for chess was implemented, and preliminary empirical results are promising.

    Original languageEnglish
    Title of host publication2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
    Pages1261-1266
    Number of pages6
    DOIs
    StatePublished - 1 Dec 2004
    Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
    Duration: 10 Oct 200413 Oct 2004

    Publication series

    NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    Volume2
    ISSN (Print)1062-922X

    Conference

    Conference2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
    Country/TerritoryNetherlands
    CityThe Hague
    Period10/10/0413/10/04

    Keywords

    • Decision-theoretic control of search
    • Game tree search
    • Planning in games

    ASJC Scopus subject areas

    • General Engineering

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