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Effects of Empathy on the Evolutionary Dynamics of Fairness in Group-Structured Systems

Author

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  • Yanling Zhang
  • Jian Liu
  • Aming Li

Abstract

The ultimatum game has been a prominent paradigm in studying the evolution of fairness. It predicts that responders should accept any nonzero offer and proposers should offer the smallest possible amount according to orthodox game theory. However, the prediction strongly contradicts with the experimental behaviors where the mean offer typically ranges from 0.3 to 0.5 and the mean demand tends to lie between 0.2 and 0.35. To explain the evolution of such fair behaviors, here we introduce empathy in a mutation-selection process with group structure and find that our results quantitatively reproduce the experimental behaviors at low randomness with intermediate empathy or relatively high randomness with small empathy. Moreover, we show that with low randomness more empathy leads to a fairer outcome with a higher mean offer and demand. Counterintuitively, more empathy corresponds to a lower mean offer together with a higher mean demand for relatively high randomness. Finally, we analytically provide the mean offer and demand under both weak and strong intensities of selection when the largest or smallest level of empathy is introduced. Our study provides systematic insights into the evolutionary origin of fairness in a mutation-selection process with empathetic strategies and group structure.

Suggested Citation

  • 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.
  • Handle: RePEc:hin:complx:2915020
    DOI: 10.1155/2019/2915020
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    References listed on IDEAS

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    1. Zhang, Yanling & Chen, Xiaojie & Liu, Aizhi & Sun, Changyin, 2018. "The effect of the stake size on the evolution of fairness," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 641-653.
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    3. Jaime Iranzo & Luis M Floría & Yamir Moreno & Angel Sánchez, 2012. "Empathy Emerges Spontaneously in the Ultimatum Game: Small Groups and Networks," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-8, September.
    4. Guth, Werner & Schmittberger, Rolf & Schwarze, Bernd, 1982. "An experimental analysis of ultimatum bargaining," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 367-388, December.
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. M. N. Kuperman & S. Risau-Gusman, 2008. "The effect of the topology on the spatial ultimatum game," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(2), pages 233-238, March.
    7. Serguei Saavedra & Felix Reed-Tsochas & Brian Uzzi, 2009. "A simple model of bipartite cooperation for ecological and organizational networks," Nature, Nature, vol. 457(7228), pages 463-466, January.
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    Cited by:

    1. 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).
    2. Chen, Wei & Zhu, Qianlong & Wu, Te, 2023. "Unfairness promotes the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    3. Gao, Shiping & Li, Nan, 2023. "Preference reversal and the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(C).

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