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Short Versus Long Term Benefits and the Evolution of Cooperation in the Prisoner's Dilemma Game

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  • Markus Brede

Abstract

In this paper I investigate the evolution of cooperation in the prisoner's dilemma when individuals change their strategies subject to performance evaluation of their neighbours over variable time horizons. In the monochrome setting, in which all agents per default share the same performance evaluation rule, weighing past events strongly dramatically enhances the prevalence of cooperators. For co-evolutionary models, in which evaluation time horizons and strategies can co-evolve, I demonstrate that cooperation naturally associates with long-term evaluation of others while defection is typically paired with very short time horizons. Moreover, considering the continuous spectrum in between enhanced and discounted weights of past performance, cooperation is optimally supported when cooperators neither give enhanced weight to past nor more recent events, but simply average payoffs. Payoff averaging is also found to emerge as the dominant strategy for cooperators in co-evolutionary models, thus proposing a natural route to the evolution of cooperation in viscous populations.

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  • Markus Brede, 2013. "Short Versus Long Term Benefits and the Evolution of Cooperation in the Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    • Handle: RePEc:plo:pone00:0056016
    DOI: 10.1371/journal.pone.0056016
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    References listed on IDEAS

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    1. Thomas Chadefaux & Dirk Helbing, 2010. "How Wealth Accumulation Can Promote Cooperation," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-7, October.
    2. Matjaž Perc & Zhen Wang, 2010. "Heterogeneous Aspirations Promote Cooperation in the Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-8, December.
    3. Francisco C Santos & Jorge M Pacheco & Tom Lenaerts, 2006. "Cooperation Prevails When Individuals Adjust Their Social Ties," PLOS Computational Biology, Public Library of Science, vol. 2(10), pages 1-8, October.
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    1. Kohei Miyaji & Jun Tanimoto & Zhen Wang & Aya Hagishima & Naoki Ikegaya, 2013. "Direct Reciprocity in Spatial Populations Enhances R-Reciprocity As Well As ST-Reciprocity," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Alam, Muntasir & Nagashima, Keisuke & Tanimoto, Jun, 2018. "Various error settings bring different noise-driven effects on network reciprocity in spatial prisoner's dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 338-346.
    3. Keizo Shigaki & Zhen Wang & Jun Tanimoto & Eriko Fukuda, 2013. "Effect of Initial Fraction of Cooperators on Cooperative Behavior in Evolutionary Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-7, November.
    4. Markus Brede, 2013. "Costly Advertising and the Evolution of Cooperation," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    5. Liu, Yifan & Geng, Yini & Du, Chunpeng & Hu, Kaipeng & Shen, Chen & Pansini, Riccardo & Shi, Lei, 2021. "The interface of unidirectional rewards: Enhanced cooperation within interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 402(C).
    6. Xie, Yunya & Bai, Yu & Zhang, Yankun & Peng, Zhengyin, 2024. "Trust-induced cooperation under the complex interaction of networks and emotions," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

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