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How Evolutionary Dynamics Affects Network Reciprocity in Prisoner’s Dilemma

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Abstract

Cooperation lies at the foundations of human societies, yet why people cooperate remains a conundrum. The issue, known as network reciprocity, of whether population structure can foster cooperative behavior in social dilemmas has been addressed by many, but theoretical studies have yielded contradictory results so far—as the problem is very sensitive to how players adapt their strategy. However, recent experiments with the prisoner’s dilemma game played on different networks and in a specific range of payoffs suggest that humans, at least for those experimental setups, do not consider neighbors’ payoffs when making their decisions, and that the network structure does not influence the final outcome. In this work we carry out an extensive analysis of different evolutionary dynamics, taking into account most of the alternatives that have been proposed so far to implement players’ strategy updating process. In this manner we show that the absence of network reciprocity is a general feature of the dynamics (among those we consider) that do not take neighbors’ payoffs into account. Our results, together with experimental evidence, hint at how to properly model real people’s behavior.

Suggested Citation

  • Giulio Cimini & Angel Sanchez, 2015. "How Evolutionary Dynamics Affects Network Reciprocity in Prisoner’s Dilemma," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-22.
  • Handle: RePEc:jas:jasssj:2014-69-3
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    File URL: https://www.jasss.org/18/2/22/22.pdf
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    Cited by:

    1. Takahiro Ezaki & Naoki Masuda, 2017. "Reinforcement learning account of network reciprocity," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-8, December.

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