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Poker as a testbed for machine intelligence research (1998)

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by Darse Billings , Jonathan Schaeffer , Duane Szafron
Venue:Advances in Artificial Intelligence
Citations:14 - 2 self
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BibTeX

@INPROCEEDINGS{Billings98pokeras,
    author = {Darse Billings and Jonathan Schaeffer and Duane Szafron},
    title = {Poker as a testbed for machine intelligence research},
    booktitle = {Advances in Artificial Intelligence},
    year = {1998},
    pages = {1--15},
    publisher = {Springer Verlag}
}

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Abstract

For years, games researchers have used chess, checkers and other board games as a testbed for machine intelligence research. The success of world-championship-caliber programs for these games has resulted in a number of interesting games being overlooked. Specifically, we show that poker can serve as a better testbed for machine intelligence research related to decision making problems. Poker 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. The heuristic search and evaluation methods successfully employed in chess are not helpful here. This paper outlines the difficulty of playing strong poker, and describes our first steps towards building a world-class poker-playing program.

Keyphrases

machine intelligence research    decision making problem    strong poker    agent modeling    interesting game    board game    game researcher    world-class poker-playing program    risk management    unreliable information    decision-making application    evaluation method    imperfect knowledge    world-championship-caliber program    heuristic search    real world    first step towards   

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