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Cooperation in the prisoner’s dilemma game on tunable community networks

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  • Liu, Penghui
  • Liu, Jing

Abstract

Community networks have attracted lots of attention as they widely exist in the real world and are essential to study properties of networks. As the game theory illustrates the competitive relationship among individuals, studying the iterated prisoner’s dilemma games (PDG) on community networks is meaningful. In this paper, we focus on investigating the relationship between the cooperation level of community networks and that of their communities in the prisoner’s dilemma games. With this purpose in mind, a type of tunable community networks whose communities inherit not only the scale-free property, but also the characteristic of adjustable cooperation level of Holme and Kim (HK) networks is designed. Both uniform and non-uniform community networks are investigated. We find out that cooperation enhancement of communities can improve the cooperation level of the whole networks. Moreover, simulation results indicate that a large community is a better choice than a small community to improve the cooperation level of the whole networks. Thus, improving the cooperation level of community networks can be divided into a number of sub-problems targeting at improving the cooperation level of individual communities, which can save the computation cost and deal with the problem of improving the cooperation level of huge community networks. Moreover, as the larger community is a better choice, it is reasonable to start with large communities, according to the greedy strategy when the number of nodes can participate in the enhancement is limited.

Suggested Citation

  • Liu, Penghui & Liu, Jing, 2017. "Cooperation in the prisoner’s dilemma game on tunable community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 156-163.
    • Handle: RePEc:eee:phsmap:v:472:y:2017:i:c:p:156-163
    DOI: 10.1016/j.physa.2016.12.059
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    References listed on IDEAS

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    1. Chen, Xiaojie & Fu, Feng & Wang, Long, 2007. "Prisoner's Dilemma on community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 512-518.
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    Cited by:

    1. Sun, Jiaqin & Fan, Ruguo & Luo, Ming & Zhang, Yingqing & Dong, Lili, 2018. "The evolution of cooperation in spatial prisoner’s dilemma game with dynamic relationship-based preferential learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 598-611.
    2. Shi, Zhenyu & Wei, Wei & Zheng, Hongwei & Zheng, Zhiming, 2023. "Bidirectional supervision: An effective method to suppress corruption and defection under the third party punishment mechanism of donation games," Applied Mathematics and Computation, Elsevier, vol. 450(C).

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