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Linear algebraic structure of zero-determinant strategies in repeated games

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  • Masahiko Ueda
  • Toshiyuki Tanaka

Abstract

Zero-determinant (ZD) strategies, a recently found novel class of strategies in repeated games, has attracted much attention in evolutionary game theory. A ZD strategy unilaterally enforces a linear relation between average payoffs of players. Although existence and evolutional stability of ZD strategies have been studied in simple games, their mathematical properties have not been well-known yet. For example, what happens when more than one players employ ZD strategies have not been clarified. In this paper, we provide a general framework for investigating situations where more than one players employ ZD strategies in terms of linear algebra. First, we theoretically prove that a set of linear relations of average payoffs enforced by ZD strategies always has solutions, which implies that incompatible linear relations are impossible. Second, we prove that linear payoff relations are independent of each other under some conditions. These results hold for general games with public monitoring including perfect-monitoring games. Furthermore, we provide a simple example of a two-player game in which one player can simultaneously enforce two linear relations, that is, simultaneously control her and her opponent’s average payoffs. All of these results elucidate general mathematical properties of ZD strategies.

Suggested Citation

  • Masahiko Ueda & Toshiyuki Tanaka, 2020. "Linear algebraic structure of zero-determinant strategies in repeated games," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.
  • Handle: RePEc:plo:pone00:0230973
    DOI: 10.1371/journal.pone.0230973
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    References listed on IDEAS

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    1. Jin-Li Guo, 2014. "Zero-determinant strategies in iterated multi-strategy games," Papers 1409.1786, arXiv.org, revised Sep 2014.
    2. Ethan Akin, 2015. "What You Gotta Know to Play Good in the Iterated Prisoner’s Dilemma," Games, MDPI, vol. 6(3), pages 1-16, June.
    3. Christoph Adami & Arend Hintze, 2013. "Evolutionary instability of zero-determinant strategies demonstrates that winning is not everything," Nature Communications, Nature, vol. 4(1), pages 1-8, October.
    4. repec:cla:levarc:786969000000001297 is not listed on IDEAS
    5. Christian Hilbe & Krishnendu Chatterjee & Martin A. Nowak, 2018. "Partners and rivals in direct reciprocity," Nature Human Behaviour, Nature, vol. 2(7), pages 469-477, July.
    6. Zhijian Wang & Yanran Zhou & Jaimie W. Lien & Jie Zheng & Bin Xu, 2016. "Extortion Can Outperform Generosity in the Iterated Prisoners' Dilemma," Levine's Bibliography 786969000000001297, UCLA Department of Economics.
    7. Hilbe, Christian & Traulsen, Arne & Sigmund, Karl, 2015. "Partners or rivals? Strategies for the iterated prisoner's dilemma," Games and Economic Behavior, Elsevier, vol. 92(C), pages 41-52.
    8. Christian Hilbe & Martin A Nowak & Arne Traulsen, 2013. "Adaptive Dynamics of Extortion and Compliance," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-9, November.
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    Cited by:

    1. Masahiko Ueda, 2022. "Controlling Conditional Expectations by Zero-Determinant Strategies," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    2. Taha, Mohammad A. & Ghoneim, Ayman, 2021. "Zero-determinant strategies in infinitely repeated three-player prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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