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Reputation-based adaptive adjustment of link weight among individuals promotes the cooperation in spatial social dilemmas

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  • Li, Xiaopeng
  • Sun, Shiwen
  • Xia, Chengyi

Abstract

The relationships among individuals on the network are often dynamic and adaptive adjustment with the interactions, which have a strong effect on the cooperation behavior. In this paper, we propose a new spatial evolutionary game model to further investigate the emergence and persistence of cooperation, in which the link weights among individuals are dynamically and adaptively adjusted by comparing between their own reputation and the average one of their nearest neighbors. If the reputation of the focal player is greater than the average one of his/her nearest neighbors, the nearest neighbors around the focal player will follow him/her, thus the link weight between the nearest neighbors and the focal player will increase by one unit as a reward. In contrast, the corresponding link weight will be decreased by one unit as a punishment. In addition, we use another parameter ε to control the possible range of link weight. By conducting extensive Monte Carlo numerical simulations in the prisoner’s dilemma and the snowdrift games, it is clearly verified that the adaptive adjustment of link weight can dramatically promote the evolution of cooperation, and the cooperation can be further elevated into a higher level when compared with the standard spatial dilemma game. The current results are helpful for us to better understand the influence of dynamic link weight on the collective cooperation behavior.

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  • Li, Xiaopeng & Sun, Shiwen & Xia, Chengyi, 2019. "Reputation-based adaptive adjustment of link weight among individuals promotes the cooperation in spatial social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 810-820.
    • Handle: RePEc:eee:apmaco:v:361:y:2019:i:c:p:810-820
    DOI: 10.1016/j.amc.2019.06.038
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    References listed on IDEAS

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