Solving Six-Player Games via Online Situation Estimation

While the artificial intelligence theory for solving the perfect-information games has been well developed in recent years, great challenges are still posed in dealing with the imperfect-information game due to the huge state space and hidden information involved in it. In this paper, we design an o...

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Bibliographic Details
Main Authors: Li, Huale, Wang, Xuan, Qi, Shuhan, Liu, Yang, Wang, Haojie, Jia, Fengwei, Zhang, Jiajia
Format: Conference Proceeding
Language:English
Subjects:
game
imperfect information
poker
six-player
Online Access:Request full text
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Summary:While the artificial intelligence theory for solving the perfect-information games has been well developed in recent years, great challenges are still posed in dealing with the imperfect-information game due to the huge state space and hidden information involved in it. In this paper, we design an online strategy solving framework for six-player no-limit Texas hold'em poker. Based on hand isomorphism and hand strength evalution, the framework provides an efficient situation estimation method for six-player poker. Such method could greatly reduce the the state space in six-player poker as well as effectively evaluate the current hands. The poker agent based on our method won the third place in the 2018 AAAI-ACPC.
ISSN:2375-0197
DOI:10.1109/ICTAI.2019.00270