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Aspiration-Based Partner Switching Boosts Cooperation in Social Dilemmas

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  • Zhi Li
  • Zhihu Yang
  • Te Wu
  • Long Wang

Abstract

Most previous studies concerning linking dynamics often assumed that links pairing individuals should be identified and treated differently during topology adjusting procedure, in order to promote cooperation. A common assumption was that cooperators were expected to avoid being exploited by quickly breaking up relationships with defectors. Then the so-called prosocial links linking two cooperators (abbreviated as CC links hereafter) would be much favored by evolution, whereby cooperation was promoted. However, we suggest that this is not always necessary. Here, we developed a minimal model in which an aspiration-based partner switching mechanism was embedded to regulate the evolution of cooperation in social dilemmas. Individuals adjusted social ties in a self-questioning manner in line with the learning theory. Less game information was involved during dynamic linking and all links were tackled anonymously irrespective of their types (i.e., CD links, DD links, or CC links). The main results indicate that cooperation flourishes for a broad range of parameters. The denser the underlying network, the more difficult the evolution of cooperation. More importantly, moderate aspirations do much better in promoting the evolution of altruistic behavior and for most cases there exists the optimal aspiration level that most benefits cooperation. Too strong or too weak selection intensity turns out to be pretty conducive to the evolution of cooperation in such a dynamical system.

Suggested Citation

  • Zhi Li & Zhihu Yang & Te Wu & Long Wang, 2014. "Aspiration-Based Partner Switching Boosts Cooperation in Social Dilemmas," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-7, June.
  • Handle: RePEc:plo:pone00:0097866
    DOI: 10.1371/journal.pone.0097866
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    Cited by:

    1. Chen, Ya-Shan & Yang, Han-Xin & Guo, Wen-Zhong, 2017. "Aspiration-induced dormancy promotes cooperation in the spatial Prisoner’s Dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 625-630.
    2. Sun, Chengbin & Luo, Chao, 2020. "Co-evolution of limited resources in the memory-based spatial evolutionary game," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    3. Chen, Wei & Wu, Te & Li, Zhiwu & Wang, Long, 2016. "Friendship-based partner switching promotes cooperation in heterogeneous populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 192-199.
    4. Xia, Ke, 2021. "The characteristics of average abundance function of multi-player threshold public goods evolutionary game model under redistribution mechanism," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    5. Wang, Qiuling & Jia, Danyang, 2019. "Expectation driven by update willingness promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 174-179.
    6. Xia, Ke, 2021. "Average abundance function of multi-player threshold public goods without initial endowment evolutionary game model under differential aspiration levels and redistribution mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).

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