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Permanent link (DOI): https://doi.org/10.7939/R3R360

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Using counterfactual regret minimization to create a competitive multiplayer poker agent Open Access

Descriptions

Other title
Subject/Keyword
poker
heads-up experts
CFR
multiplayer
counterfactual regret minimization
poki
3-player
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Abou Risk, Nicholas
Supervisor and department
Szafron, Duane (Computing Science)
Examining committee member and department
Carbonaro, Mike (Educational Psychology)
Holte, Rob (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2009-10-02T20:38:47Z
Graduation date
2009-11
Degree
Master of Science
Degree level
Master's
Abstract
Games have been used to evaluate and advance techniques in the field of Artificial Intelligence since before computers were invented. Many of these games have been deterministic perfect information games (e.g. Chess and Checkers). A deterministic game has no chance element and in a perfect information game, all information is visible to all players. However, many real-world scenarios involving competing agents can be more accurately modeled as stochastic (non-deterministic), im- perfect information games, and this dissertation investigates such games. Poker is one such game played by millions of people around the world; it will be used as the testbed of the research presented in this dissertation. For a specific set of games, two-player zero-sum perfect recall games, a recent technique called Counterfactual Regret Minimization (CFR) computes strategies that are provably convergent to an ϵ-Nash equilibrium. A Nash equilibrium strategy is very useful in two-player games as it maximizes its utility against a worst-case opponent. However, once we move to multiplayer games, we lose all theoretical guarantees for CFR. Furthermore, we have no theoretical guarantees about the performance of a strategy from a multiplayer Nash equilibrium against two arbitrary op- ponents. Despite the lack of theoretical guarantees, my thesis is that CFR-generated agents may perform well in multiplayer games. I created several 3-player limit Texas Hold’em Poker agents and the results of the 2009 Computer Poker Competition demonstrate that these are the strongest 3-player computer Poker agents in the world. I also contend that a good strategy can be obtained by grafting a set of two-player subgame strategies to a 3-player base strategy when one of the players is eliminated.
Language
English
DOI
doi:10.7939/R3R360
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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