Computing card probabilities in Texas Hold'em

Developing Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to esti...

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Bibliographic Details
Main Authors: Teofilo, Luis Filipe, Reis, Luis Paulo, Lopes Cardoso, Henrique
Format: Conference Proceeding
Language:English
Subjects:
Communities
Computational modeling
Computer Poker
Educational institutions
Game state abstraction
Games
Incomplete information games
Indexes
Opponent modeling
Poker hand probabilities
Rivers
Table lookup
Texas Hold'em Poker
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Summary:Developing Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to estimate their game plan and make decisions based on such estimations. In this paper, several hand evaluation and classification techniques are compared and conclusions on their respective applicability and scope are drawn. Also, we suggest improvements on current techniques through Monte Carlo sampling. The current methods to deal with risk management were found to be pertinent concerning the agent's decision-making process; nevertheless future integration of these methods with opponent modeling techniques can greatly improve overall Poker agents' performance.
ISSN:2166-0727