4.6 Article

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

期刊

出版社

ELSEVIER
DOI: 10.1016/j.physa.2016.12.059

关键词

Tunable community networks; Prisoner's dilemma; Cooperation

资金

  1. Outstanding Young Scholar Program of National Natural Science Foundation of China (NSFC) [61522311]
  2. General Program of NSFC [61271301]
  3. Overseas, Hong Kong & Macao Scholars Collaborated Research Program of NSFC [61528205]
  4. Research Fund for the Doctoral Program of Higher Education of China [20130203110010]
  5. Fundamental Research Funds for the Central Universities [K5051202052]

向作者/读者索取更多资源

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. (C) 2016 Elsevier B.V. All rights reserved.

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