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How the indirect reciprocity with co-evolving norm and strategy for 2 × 2 prisoner’s dilemma game works for emerging cooperation

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  • Tanimoto, Jun
  • Sagara, Hirokji

Abstract

We built a new indirect reciprocity model based on binary image scores, where an agent’s strategy and norm co-evolve. The norm, meaning what behavior is evaluated as “good” or “bad,” stipulates how image scores of two agents playing a game is altered, which has been presumed to be a fixed value in most previous studies. Also, unlike former studies, our model allows an agent to play with an agent who has a different norm. This point of relaxing the freedom of the model pulls down cooperation level vis-à-vis the case where an agent always plays with another one having same norm. However, it is observed that a rather larger dilemma shows robust cooperation establishing compared with a smaller dilemma, since a norm that punishes a so-called second-order free-rider is prompted. To encourage the evolution of norms to be able to punish second-order free-riders, a society needs a small number of defectors. This is elucidated by the fact that cases with action error are more cooperative than those without action error.

Suggested Citation

  • Tanimoto, Jun & Sagara, Hirokji, 2015. "How the indirect reciprocity with co-evolving norm and strategy for 2 × 2 prisoner’s dilemma game works for emerging cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 595-602.
    • Handle: RePEc:eee:phsmap:v:438:y:2015:i:c:p:595-602
    DOI: 10.1016/j.physa.2015.07.006
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    Cited by:

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    2. Mao, Fubing & Ma, Lijia & He, Qiang & Xiao, Gaoxi, 2020. "Match making in complex social networks," Applied Mathematics and Computation, Elsevier, vol. 371(C).

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