Martin Schmid, Matej Moravčík, Milan Hladík, and Stephen J. Gaukroder. Automatic public state space abstraction in imperfect information games. In Computer Poker and Imperfect Information: Papers from the 2015 AAAI Workshop, pp. 51–56, AAAI Press, 2015.
Although techniques for finding Nash equilibria in extensive form games have become more powerful in recent years, many games that model real world interactions remain too large to be solved directly. The current approach is to create a smaller abstracted game, allowing the computation of an optimal solution. The strategy can then be used in the original game. Considering public information to create the abstraction can be strategically important, yet very few of the previous abstraction algorithms specifically consider public information or use an expert approach. In this paper, we show that the public information can be crucial, and we present a new, automatic technique for abstracting the public state space. We also present an experimental evaluation in the domain of Texas Hold'em poker and show that it outperforms state-of-the-art abstraction algorithms.
@inProceedings{SchmMor2015a,
author = "Martin Schmid and Matej Morav{\v{c}}\'{\i}k and Milan Hlad\'{\i}k and Stephen J. Gaukroder",
title = "Automatic public state space abstraction in imperfect information games",
booktitle = "Computer Poker and Imperfect Information: Papers from the 2015 AAAI Workshop",
publisher = "AAAI Press",
pages = "51-56",
year = "2015",
isbn = "978-1-57735-718-6",
bib2html_dl_pdf = "http://www.aaai.org/ocs/index.php/WS/AAAIW15/paper/view/10073",
abstract = "Although techniques for finding Nash equilibria in extensive form games have become more powerful in recent years, many games that model real world interactions remain too large to be solved directly. The current approach is to create a smaller abstracted game, allowing the computation of an optimal solution. The strategy can then be used in the original game. Considering public information to create the abstraction can be strategically important, yet very few of the previous abstraction algorithms specifically consider public information or use an expert approach. In this paper, we show that the public information can be crucial, and we present a new, automatic technique for abstracting the public state space. We also present an experimental evaluation in the domain of Texas Hold'em poker and show that it outperforms state-of-the-art abstraction algorithms.",
keywords = "Game theory; Poker; Nash Equilibrium; Abstraction; Public Information",
}
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