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Evolutionary prisoner’s dilemma game on weighted scale-free networks

Author

Listed:
  • Du, Wen-Bo
  • Zheng, Hao-Ran
  • Hu, Mao-Bin

Abstract

This paper investigates the evolutionary prisoner’s dilemma on weighted scale-free networks. The weighted networks are generated by adopting Barabási–Albert scale-free network and assigning link weight with wij=(ki×kj)β. Simulation results show that the cooperation frequency has a strong dependence on β. The value of β which is associated with the maximal cooperation frequency has been sought out. Moreover, Gini coefficient and Pareto exponent of the system’s wealth distribution are investigated. The inequality of wealth distribution is minimized at β≈−1.

Suggested Citation

  • Du, Wen-Bo & Zheng, Hao-Ran & Hu, Mao-Bin, 2008. "Evolutionary prisoner’s dilemma game on weighted scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3796-3800.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:14:p:3796-3800
    DOI: 10.1016/j.physa.2008.02.036
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    Citations

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    Cited by:

    1. Cui, Guang-Hai & Wang, Zhen & Yang, Yan-Cun & Tian, Sheng-Wen & Yue, Jun, 2018. "Heterogeneous game resource distributions promote cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1191-1200.
    2. 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.
    3. Wu, Jianshe & Hou, Yanqiao & Jiao, Licheng & Li, Huijie, 2014. "Community structure inhibits cooperation in the spatial prisoner’s dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 169-179.
    4. Iwata, Manabu & Akiyama, Eizo, 2016. "Heterogeneity of link weight and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 224-234.
    5. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2021. "Effects of defensive cooperation strategy on the evolution of cooperation in social dilemma," Applied Mathematics and Computation, Elsevier, vol. 399(C).
    6. Buesser, Pierre & Peña, Jorge & Pestelacci, Enea & Tomassini, Marco, 2011. "The influence of tie strength on evolutionary games on networks: An empirical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4502-4513.
    7. Fan, Wenli & Huang, Shaowei & Mei, Shengwei, 2016. "Invulnerability of power grids based on maximum flow theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 977-985.
    8. Griffin, Christopher & Semonsen, Justin & Belmonte, Andrew, 2022. "Generalized Hamiltonian dynamics and chaos in evolutionary games on networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    9. Pan, Qiuhui & Wang, Linpeng & He, Mingfeng, 2020. "Social dilemma based on reputation and successive behavior," Applied Mathematics and Computation, Elsevier, vol. 384(C).
    10. Swami Iyer & Timothy Killingback, 2020. "Evolution of Cooperation in Social Dilemmas with Assortative Interactions," Games, MDPI, vol. 11(4), pages 1-31, September.
    11. Yang, Zhengzhi & Zheng, Lei & Perc, Matjaž & Li, Yumeng, 2024. "Interaction state Q-learning promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 463(C).

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