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A Survey on Game Theory Optimal Poker

arXiv 2401.06168 ↗First posted 2 Jan 2024cs.GT cs.AIcited by 0

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Abstract (arXiv)

Poker is in the family of imperfect information games unlike other games such as chess, connect four, etc which are perfect information game instead. While many perfect information games have been solved, no non-trivial imperfect information game has been solved to date. This makes poker a great test bed for Artificial Intelligence research. In this paper we firstly compare Game theory optimal poker to Exploitative poker. Secondly, we discuss the intricacies of abstraction techniques, betting models, and specific strategies employed by successful poker bots like Tartanian[1] and Pluribus[6]. Thirdly, we also explore 2-player vs multi-player games and the limitations that come when playing with more players. Finally, this paper discusses the role of machine learning and theoretical approaches in developing winning strategies and suggests future directions for this rapidly evolving field.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 8 references that are in the map. First posted on arXiv 2 Jan 2024.

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References · 1

  1. 2020Combining Deep Reinforcement Learning and Search for Imperfect-Information Gamescited by 114

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