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Strategy intervention for the evolution of fairness

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  • Yanling Zhang
  • Feng Fu

Abstract

The ‘irrational’ preference for fairness has attracted increasing attention. Although previous studies have focused on the effects of spitefulness on the evolution of fairness, they did not consider non-monotonic rejections shown in behavioral experiments. In this paper, we introduce a non-monotonic rejection in an evolutionary model of the Ultimatum Game. We propose strategy intervention to study the evolution of fairness in general structured populations. By sequentially adding five strategies into the competition between a fair strategy and a selfish strategy, we arrive at the following conclusions. First, the evolution of fairness is inhibited by altruism, but it is promoted by spitefulness. Second, the non-monotonic rejection helps fairness overcome selfishness. Particularly for group-structured populations, we analytically investigate how fairness, selfishness, altruism, and spitefulness are affected by population size, mutation, and migration in the competition among seven strategies. Our results may provide important insights into understanding the evolutionary origin of fairness.

Suggested Citation

  • Yanling Zhang & Feng Fu, 2018. "Strategy intervention for the evolution of fairness," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0196524
    DOI: 10.1371/journal.pone.0196524
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    2. Zhao, Yakun & Xiong, Tianyu & Zheng, Lei & Li, Yumeng & Chen, Xiaojie, 2020. "The effect of similarity on the evolution of fairness in the ultimatum game," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
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    4. Yanling Zhang & Jian Liu & Aming Li, 2019. "Effects of Empathy on the Evolutionary Dynamics of Fairness in Group-Structured Systems," Complexity, Hindawi, vol. 2019, pages 1-13, November.
    5. Zhang, Yanling & Yang, Shuo & Chen, Xiaojie & Bai, Yanbing & Xie, Guangming, 2023. "Reputation update of responders efficiently promotes the evolution of fairness in the ultimatum game," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Chen, Wei & Zhu, Qianlong & Wu, Te, 2023. "Unfairness promotes the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(C).
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    8. Li, Kun & Mao, Yizhou & Wei, Zhenlin & Cong, Rui, 2021. "Pool-rewarding in N-person snowdrift game," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    9. Kang, Zengxin & Zhang, Lei & Li, Kun, 2019. "An improved social force model for pedestrian dynamics in shipwrecks," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 355-362.

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