Opponent Modeling in Poker

Abstract

Poker is an interesting test-bed for artificial intelligence research. It is a game of imperfect knowledge, where multiple competing agents must deal with risk management, agent modeling, unreliable information and deception, much like decision-making applications in the real world. Agent modeling is one of the most difficult problems in decision-making applications and in poker it is essential to achieving high performance. This paper describes and evaluates Loki, a poker program capable of observing its opponents, constructing opponent models and dynamically adapting its play to best exploit patterns in the opponents’ play.

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Cite this paper

@inproceedings{Billings1998OpponentMI, title={Opponent Modeling in Poker}, author={Darse Billings and Denis Papp and Jonathan Schaeffer and Duane Szafron}, booktitle={AAAI/IAAI}, year={1998} }