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Extortion subdues human players but is finally punished in the prisoner’s dilemma

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  • Christian Hilbe

    (Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology
    Program for Evolutionary Dynamics, Harvard University)

  • Torsten Röhl

    (Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology)

  • Manfred Milinski

    (Max-Planck-Institute for Evolutionary Biology)

Abstract

Extortion is the practice of obtaining advantages through explicit forces and threats. Recently, it was demonstrated that even the repeated prisoner’s dilemma, one of the key models to explain mutual cooperation, allows for implicit forms of extortion. According to the theory, extortioners demand and receive an excessive share of any surplus, which allows them to outperform any adapting co-player. To explore the performance of such strategies against humans, we have designed an economic experiment in which participants were matched either with an extortioner or with a generous co-player. Although extortioners succeeded against each of their human opponents, extortion resulted in lower payoffs than generosity. Human subjects showed a strong concern for fairness: they punished extortion by refusing to fully cooperate, thereby reducing their own, and even more so, the extortioner’s gains. Thus, the prospects of extorting others in social relationships seem limited; in the long run, generosity is more profitable.

Suggested Citation

  • Christian Hilbe & Torsten Röhl & Manfred Milinski, 2014. "Extortion subdues human players but is finally punished in the prisoner’s dilemma," Nature Communications, Nature, vol. 5(1), pages 1-6, September.
  • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4976
    DOI: 10.1038/ncomms4976
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    Cited by:

    1. Wang, Chaoqian & Huang, Chaochao & Pan, Qiuhui & He, Mingfeng, 2022. "Modeling the social dilemma of involution on a square lattice," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    2. Kang, Kai & Tian, Jinyan & Zhang, Boyu, 2024. "Cooperation and control in asymmetric repeated games," Applied Mathematics and Computation, Elsevier, vol. 470(C).
    3. Feng, Tian-Jiao & Fan, Song-Jia & Li, Cong & Tao, Yi & Zheng, Xiu-Deng, 2023. "Noise-induced sustainability of cooperation in Prisoner's Dilemma game," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    4. Feng, Sinan & Liu, Xuesong, 2024. "Effects of three-faced strategy on the evolution of cooperation in social dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    5. Masahiko Ueda, 2022. "Controlling Conditional Expectations by Zero-Determinant Strategies," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    6. Jin-Li Guo, 2014. "Zero-determinant strategies in iterated multi-strategy games," Papers 1409.1786, arXiv.org, revised Sep 2014.
    7. Xiang Wei & Peng Xu & Shuiting Du & Guanghui Yan & Huayan Pei, 2021. "Reputational preference-based payoff punishment promotes cooperation in spatial social dilemmas," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(10), pages 1-7, October.
    8. Xie, Kai & Liu, Xingwen & Wang, Huazhang & Jiang, Yulian, 2023. "Multi-heterogeneity public goods evolutionary game on lattice," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    9. Pan, Qiuhui & Wang, Linpeng & He, Mingfeng, 2020. "Social dilemma based on reputation and successive behavior," Applied Mathematics and Computation, Elsevier, vol. 384(C).
    10. Jun Qian & Tongda Zhang & Xiao Sun & Yueting Chai, 2023. "The coordination of collective and individual solutions in risk-resistant scenarios," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-15, February.

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