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The effect of multigame on cooperation in spatial network

Author

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  • Li, Zhibin
  • Jia, Danyang
  • Guo, Hao
  • Geng, Yini
  • Shen, Chen
  • Wang, Zhen
  • Li, Xuelong

Abstract

In real world, cooperation among unrelated agents remains to represent one open challenge in many disciplines. In some cases, subjects can even change their social dilemmas to ensure their own benefit. Inspired by this fact, here we propose a multigame (composed of prisoner's dilemma game and snowdrift game) and its coevolution mechanism in networked populations: if a player succeeds to study the strategy of its opponent, it also learns the game type of its opponent. Based on numerous computation simulations, it is unveiled that compared with the setup of multigame, coevolution mechanism can effectively resolve the problem of collective cooperation. While for this observation, it is attributed to the fact that vast majority of players changed their games to snowdrift game (i.e. lower social dilemma), where cooperation-defection bistable state guarantees cooperation clusters. We hope our finding can inspire more studies for resolving the social dilemmas.

Suggested Citation

  • Li, Zhibin & Jia, Danyang & Guo, Hao & Geng, Yini & Shen, Chen & Wang, Zhen & Li, Xuelong, 2019. "The effect of multigame on cooperation in spatial network," Applied Mathematics and Computation, Elsevier, vol. 351(C), pages 162-167.
    • Handle: RePEc:eee:apmaco:v:351:y:2019:i:c:p:162-167
    DOI: 10.1016/j.amc.2018.12.059
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