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From Local to Global Dilemmas in Social Networks

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  • Flávio L Pinheiro
  • Jorge M Pacheco
  • Francisco C Santos

Abstract

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive. Here we study the evolution of cooperation in networked populations and let individuals interact via a 2-person Prisoner's Dilemma – a characteristic defection dominant social dilemma of cooperation. We show how homogeneous networks transform a Prisoner's Dilemma into a population-wide evolutionary dynamics that promotes the coexistence between cooperators and defectors, while heterogeneous networks promote their coordination. To this end, we define a dynamic variable that allows us to track the self-organization of cooperators when co-evolving with defectors in networked populations. Using the same variable, we show how the global dynamics — and effective dilemma — co-evolves with the motifs of cooperators in the population, the overall emergence of cooperation depending sensitively on this co-evolution.

Suggested Citation

  • Flávio L Pinheiro & Jorge M Pacheco & Francisco C Santos, 2012. "From Local to Global Dilemmas in Social Networks," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-6, February.
  • Handle: RePEc:plo:pone00:0032114
    DOI: 10.1371/journal.pone.0032114
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    References listed on IDEAS

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    Cited by:

    1. Wes Maciejewski & Feng Fu & Christoph Hauert, 2014. "Evolutionary Game Dynamics in Populations with Heterogenous Structures," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-16, April.
    2. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    3. Sarkar, Bijan, 2018. "Moran-evolution of cooperation: From well-mixed to heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 319-334.
    4. Dai, Qionglin & Li, Haihong & Cheng, Hongyan & Zhang, Mei & Yang, Junzhong, 2013. "The effects of nonlinear imitation probability on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 53-58.
    5. Shuhua Chang & Zhipeng Zhang & Yu Li & Yu E Wu & Yunya Xie, 2018. "Investment preference promotes cooperation in spatial public goods game," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-14, November.
    6. Li, Zhi & Deng, Chuang & Suh, Il Hong, 2015. "Network topology control strategy based on spatial evolutionary public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 16-23.
    7. Yang, Guoli & Wu, Yu'e & Cavaliere, Matteo, 2024. "Information-driven cooperation on adaptive cyber-physical systems," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    8. Boyu Zhang & Cong Li & Yi Tao, 2016. "Evolutionary Stability and the Evolution of Cooperation on Heterogeneous Graphs," Dynamic Games and Applications, Springer, vol. 6(4), pages 567-579, December.
    9. Jeromos Vukov & Flávio L Pinheiro & Francisco C Santos & Jorge M Pacheco, 2013. "Reward from Punishment Does Not Emerge at All Costs," PLOS Computational Biology, Public Library of Science, vol. 9(1), pages 1-6, January.

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