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Evolutionary game on a stochastic growth network

Author

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  • Li, Gang
  • Jin, Xiao-Gang
  • Song, Zhi-Huan

Abstract

In some real complex systems the structures are difficult to map or changing over time. To explore the evolution of strategies on these complex systems, it is not realistic enough to specify their structures or topological properties in advance. In this paper, we address the evolutionary game on a stochastic growth network adopting the prisoner’s dilemma game. We introduce a growing rate q to control the ratio of network growth to strategy evolution. A large q denotes that the network grows faster than strategy evolution. Simulation results show that a fast growing rate is helpful to promote the average payoffs of both cooperators and defectors. Moreover, this parameter also significantly influences the cooperation frequency on the resulting networks. The coexisting mechanisms in this paper may provide a beneficial insight for understanding the emergence of complex topological structures and game behaviors in numerous real systems.

Suggested Citation

  • Li, Gang & Jin, Xiao-Gang & Song, Zhi-Huan, 2012. "Evolutionary game on a stochastic growth network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6664-6673.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:24:p:6664-6673
    DOI: 10.1016/j.physa.2012.07.057
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    References listed on IDEAS

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    1. Szolnoki, Attila & Perc, Matjaž & Danku, Zsuzsa, 2008. "Towards effective payoffs in the prisoner’s dilemma game on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2075-2082.
    2. Wu, Zhi-Xi & Guan, Jian-Yue & Xu, Xin-Jian & Wang, Ying-Hai, 2007. "Evolutionary prisoner's dilemma game on Barabási–Albert scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 672-680.
    3. Qin, Shao-Meng & Zhang, Guo-Yong & Chen, Yong, 2009. "Coevolution of game and network structure with adjustable linking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4893-4900.
    4. A. Szolnoki & M. Perc, 2009. "Promoting cooperation in social dilemmas via simple coevolutionary rules," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 337-344, February.
    5. Fu, Feng & Chen, Xiaojie & Liu, Lianghuan & Wang, Long, 2007. "Promotion of cooperation induced by the interplay between structure and game dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 651-659.
    6. Julia Poncela & Jesús Gómez-Gardeñes & Luis M Floría & Angel Sánchez & Yamir Moreno, 2008. "Complex Cooperative Networks from Evolutionary Preferential Attachment," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-6, June.
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    Cited by:

    1. Li, Gang & Sun, Xiaochen, 2021. "Evolutionary game on a growing multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    2. 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).

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