Artificial Intelligence and Game Theory in No-Limit Texas Hold’em Poker
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Perustieteiden korkeakoulu |
Bachelor's thesis
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Authors
Date
2024-04-26
Department
Major/Subject
Data Science
Mcode
SCI3095
Degree programme
Aalto Bachelor’s Programme in Science and Technology
Language
en
Pages
28
Series
Abstract
As with many board and card games, researchers have attempted to solve poker using both game theory and artificial intelligence (AI). However, poker is an incomplete information game that is often played with over two players, meaning that solving the game becomes more complex than for complete information heads-up (two-player) games, such as chess. For several decades, efforts to develop a superhuman AI in multiplayer poker were unsuccessful, until recently when first such AI was created. Despite that, multiplayer poker is still not completely solved, and many computational and game-theoretical challenges persist. The no-limit Texas hold’em is a game-theoretically complex and captivating version of poker, including computationally challenging aspects such as imperfect information and multiplayer dynamics. Additionally, no-limit hold’em is currently the most popular version of poker, thus receiving more focus academically as well. The thesis studies AI and game theory in no-limit Texas hold’em poker as well as the computational challenges associated with the AI models by conducting a literature review of the relevant sources in the field. The paper covers the theoretical aspects of game theory in relation to poker as well as the technological advancements in developing a competitive poker model. The algorithm used in current state-of-the-art models, counterfactual regret minimization, is discussed in more detail. Due to the computational difficul- ties with no-limit hold’em game tree, several optimizations, such as abstractions and improved versions of counterfactual regret minimization must be utilized to create a capable AI for no-limit hold’em poker.Description
Supervisor
Korpi-Lagg, MaaritThesis advisor
Rintanen, JussiKeywords
4, incomplete information, poker, artifical intelligence, game theory