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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Fuzzeval: A Fuzzy Controller-Based Approach in Adaptive Learning for Backgammon Game
verfasst von : Mikael Heinze, Daniel Ortiz-Arroyo, Henrik Legind Larsen, Francisco Rodriguez-Henriquez
Erschienen in: MICAI 2005: Advances in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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In this paper we investigate the effectiveness of applying fuzzy controllers to create strong computer player programs in the domain of backgammon.
Fuzzeval,
our proposed mechanism, consists of a fuzzy controller that dynamically evaluates the perceived strength of the board configurations it receives. Fuzzeval employs an evaluation function that adjusts the membership functions linked to the linguistic variables employed in the knowledge base. The membership functions are aligned to the average crisp input that was successfully used in the past winning games. Fuzzeval mechanisms are adaptive and have the simplicity associated with fuzzy controllers. Our experiments show that Fuzzeval improves its performance up to 42% after a match of only one hundred backgammon games played against
Pubeval,
a strong intermediate level program.