Künstliche Intelligenz 25(1) - März 2011

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Zeitschriftenartikel
Heuristic Evaluation Functions for General Game Playing
(KI - Künstliche Intelligenz: Vol. 25, No. 1, 2011) Clune, James E.
This dissertation explores the problem of constructing an effective general game-playing program, with an emphasis on techniques for automatically constructing effective heuristic evaluation functions from game descriptions. A technique based on abstract models of games is presented. The abstract model treats mobility, payoff and termination as the most salient elements of a game. Each of these aspects are quantified in terms of stable features. Evidence is presented that the technique produces heuristic evaluation functions that are both comprehensible and effective. Empirical work includes a series of general game-playing programs that placed first or second for the three consecutive years of the AAAI General Game-Playing Competition.The full dissertation can be downloaded at https://sites.google.com/site/jimcluneresearch/.