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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Opponent Type Adaptation for Case-Based Strategies in Adversarial Games
verfasst von : Jonathan Rubin, Ian Watson
Erschienen in: Case-Based Reasoning Research and Development
Verlag: Springer Berlin Heidelberg
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We describe an approach for producing exploitive and adaptive
case-based strategies
in adversarial games. We describe how
adaptation
can be applied to a precomputed, static
case-based strategy
in order to allow the strategy to rapidly respond to changes in an opponent’s playing style. The exploitive strategies produced by this approach tend to
hover
around a precomputed solid strategy and adaptation is applied directly to the precomputed strategy once enough information has been gathered to classify the current
opponent type
. The use of a precomputed,
seed
strategy avoids performance degradation that can take place when little is known about an opponent. This allows our approach an advantage over other exploitive strategies whose playing decisions rely on large, individual opponent models constructed from scratch. We evaluate the approach within the experimental domain of two-player Limit Texas Hold’em poker.