Poker games provide a useful testbed for modern Artificial Intelligence techniques. Unlike many classical game domains such as chess and checkers, poker includes elements of imperfect information, stochastic events, and one or more adversarial agents to interact with. Furthermore, in poker it is possible to win or lose by varying degrees. Therefore, it can be advantageous to adapt ones' strategy to exploit a weak opponent. A poker agent must address these challenges, acting in uncertain environments and exploiting other agents, in order to be highly successful. Arguably, poker games more closely resemble many real world problems than games with perfect information. In this brief paper, we outline Polaris, a Texas Hold'em poker program. Polaris recently defeated top human professionals at the Man vs. Machine Poker Championship and it is currently the reigning AAAI Computer Poker Competition winner in the limit equilibrium and no-limit events.

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Cited By

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Bard NHawkin JRubin JZinkevich M(2013)The Annual Computer Poker CompetitionAI Magazine10.1609/aimag.v34i2.247434:2(112-114)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1609/aimag.v34i2.2474
Rubin JWatson I(2011)Successful performance via decision generalisation in no limit texas hold'emProceedings of the 19th international conference on Case-Based Reasoning Research and Development10.1007/978-3-642-23291-6_34(467-481)Online publication date: 12-Sep-2011
https://dl.acm.org/doi/10.1007/978-3-642-23291-6_34

Index Terms

A demonstration of the Polaris poker system
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
    2. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
  2. Modeling and simulation
    1. Model development and analysis
      1. Model verification and validation
      2. Modeling methodologies
2. Theory of computation
  1. Logic

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Information & Contributors

Information

Published In

AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2

May 2009

730 pages

ISBN:9780981738178

General Chairs:
Carles Sierra
Artificial Intelligence Research Institute of the Spanish Research Council (Spain)
,
Cristiano Castelfranchi
ISTC-CNR (Italy)
,
Program Chairs:
Keith S. Decker
University of Delaware
,
Jaime Simão Sichman
Politecnic School, University of São Paulo (Brazil)

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 10 May 2009

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Bard NHawkin JRubin JZinkevich M(2013)The Annual Computer Poker CompetitionAI Magazine10.1609/aimag.v34i2.247434:2(112-114)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1609/aimag.v34i2.2474
Rubin JWatson I(2011)Successful performance via decision generalisation in no limit texas hold'emProceedings of the 19th international conference on Case-Based Reasoning Research and Development10.1007/978-3-642-23291-6_34(467-481)Online publication date: 12-Sep-2011
https://dl.acm.org/doi/10.1007/978-3-642-23291-6_34

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Poker-CNN: a pattern learning strategy for making draws and bets in poker games using convolutional networks

Construction of poker playing system considering strategies

A Profitable Online No-Limit Poker Playing Agent