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Human strategic decision making in parametrized games

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  • Sam Ganzfried

Abstract

Many real-world games contain parameters which can affect payoffs, action spaces, and information states. For fixed values of the parameters, the game can be solved using standard algorithms. However, in many settings agents must act without knowing the values of the parameters that will be encountered in advance. Often the decisions must be made by a human under time and resource constraints, and it is unrealistic to assume that a human can solve the game in real time. We present a new framework that enables human decision makers to make fast decisions without the aid of real-time solvers. We demonstrate applicability to a variety of situations including settings with multiple players and imperfect information.

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  • Sam Ganzfried, 2021. "Human strategic decision making in parametrized games," Papers 2104.14744, arXiv.org, revised Nov 2021.
    • Handle: RePEc:arx:papers:2104.14744
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    File URL: http://arxiv.org/pdf/2104.14744
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    References listed on IDEAS

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    1. Sam Ganzfried & Max Chiswick, 2019. "Most Important Fundamental Rule of Poker Strategy," Papers 1906.09895, arXiv.org, revised Feb 2020.
    2. János Flesch & Arkadi Predtetchinski, 2020. "Parameterized games of perfect information," Annals of Operations Research, Springer, vol. 287(2), pages 683-699, April.
    3. Sam Ganzfried & Farzana Yusuf, 2017. "Computing Human-Understandable Strategies: Deducing Fundamental Rules of Poker Strategy," Games, MDPI, vol. 8(4), pages 1-13, November.
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    1. Sam Ganzfried, 2022. "Human Strategic Decision Making in Parametrized Games," Mathematics, MDPI, vol. 10(7), pages 1-23, April.
    2. Sam Ganzfried & Max Chiswick, 2019. "Most Important Fundamental Rule of Poker Strategy," Papers 1906.09895, arXiv.org, revised Feb 2020.

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