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Generous cooperators can outperform non-generous cooperators when replacing a population of defectors

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  • Kurokawa, Shun
  • Wakano, Joe Yuichiro
  • Ihara, Yasuo

Abstract

The evolution of cooperation has been a major challenge in evolutionary biology. Unconditional cooperators who help others at a cost to themselves are exploited by defectors who enjoy the benefits without any help in return. It has been argued that cooperation can be established in repeated dyadic interactions if cooperators punish defectors by withholding future cooperation. In social interactions involving more than two individuals, however, withholding future cooperation may result in penalizing not only defectors but also other cooperators. Hence, in such social interactions, it is unclear whether cooperation is most likely to evolve when cooperators are intolerant of any defectors. Here we show, by analyzing a stochastic model of n-player Prisoner’s Dilemma, that the evolution of cooperation can be more likely when cooperators tolerate some defection than when they have no such generosity. We also specify the optimal level of generosity that most likely facilitates the evolution of cooperation.

Suggested Citation

  • Kurokawa, Shun & Wakano, Joe Yuichiro & Ihara, Yasuo, 2010. "Generous cooperators can outperform non-generous cooperators when replacing a population of defectors," Theoretical Population Biology, Elsevier, vol. 77(4), pages 257-262.
    • Handle: RePEc:eee:thpobi:v:77:y:2010:i:4:p:257-262
    DOI: 10.1016/j.tpb.2010.03.002
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    References listed on IDEAS

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    1. 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.
    2. Suzuki, Shinsuke & Akiyama, Eizo, 2008. "Evolutionary stability of first-order-information indirect reciprocity in sizable groups," Theoretical Population Biology, Elsevier, vol. 73(3), pages 426-436.
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    Cited by:

    1. Kurokawa, Shun, 2023. "Disbandment rules that most facilitate the evolution of cooperation," Theoretical Population Biology, Elsevier, vol. 154(C), pages 79-93.
    2. Ozgur Aydogmus & Erkan Gürpinar, 2022. "Science, Technology and Institutional Change in Knowledge Production: An Evolutionary Game Theoretic Framework," Dynamic Games and Applications, Springer, vol. 12(4), pages 1163-1188, December.
    3. Deng, Kuiying & Li, Zhuozheng & Kurokawa, Shun & Chu, Tianguang, 2012. "Rare but severe concerted punishment that favors cooperation," Theoretical Population Biology, Elsevier, vol. 81(4), pages 284-291.
    4. Kurokawa, Shun, 2022. "Evolution of trustfulness in the case where resources for cooperation are sometimes absent," Theoretical Population Biology, Elsevier, vol. 145(C), pages 63-79.
    5. Fukutomi, Masao & Kurokawa, Shun, 2018. "How much cost should reciprocators pay in order to distinguish the opponent's cooperation from the opponent's defection?," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 301-314.
    6. Shun Kurokawa & Joe Yuichiro Wakano & Yasuo Ihara, 2018. "Evolution of Groupwise Cooperation: Generosity, Paradoxical Behavior, and Non-Linear Payoff Functions," Games, MDPI, vol. 9(4), pages 1-24, December.
    7. Kurokawa, Shun, 2019. "How memory cost, switching cost, and payoff non-linearity affect the evolution of persistence," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 174-192.
    8. Sekiguchi, Takuya, 2013. "General conditions for strategy abundance through a self-referential mechanism under weak selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2886-2892.
    9. Kurokawa, Shun & Ihara, Yasuo, 2013. "Evolution of social behavior in finite populations: A payoff transformation in general n-player games and its implications," Theoretical Population Biology, Elsevier, vol. 84(C), pages 1-8.

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