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Heterogeneity of allocation promotes cooperation in public goods games

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  • Lei, Chuang
  • Wu, Te
  • Jia, Jian-Yuan
  • Cong, Rui
  • Wang, Long

Abstract

We investigate the effects of heterogeneous investment and distribution on the evolution of cooperation in the context of the public goods games. To do this, we develop a simple model in which each individual allocates differing funds to his direct neighbors based upon their difference in connectivity, because of the heterogeneity of real social ties. This difference is characterized by the weight of the link between paired individuals, with an adjustable parameter precisely controlling the heterogeneous level of ties. By numerical simulations, it is found that allocating both too much and too little funds to diverse neighbors can remarkably improve the cooperation level. However, there exists a worst mode of funds allocation leading to the most unfavorable cooperation induced by the moderate values of the parameter. In order to better reveal the potential causes behind these nontrivial phenomena we probe the microscopic characteristics including the average payoff and the cooperator density for individuals of different degrees. It demonstrates rather different dynamical behaviors between the modes of these two types of cooperation promoter. Besides, we also investigate the total link weights of individuals numerically and theoretically for negative values of the parameter, and conclude that the payoff magnitude of middle-degree nodes plays a crucial role in determining the cooperators’ fate.

Suggested Citation

  • Lei, Chuang & Wu, Te & Jia, Jian-Yuan & Cong, Rui & Wang, Long, 2010. "Heterogeneity of allocation promotes cooperation in public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4708-4714.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:21:p:4708-4714
    DOI: 10.1016/j.physa.2010.06.002
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    References listed on IDEAS

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    1. Ken Binmore, 1994. "Game Theory and the Social Contract, Volume 1: Playing Fair," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262023636, December.
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    Cited by:

    1. Deng, Lili & Zhang, Xingxing & Wang, Cheng, 2021. "Coevolution of spatial ultimatum game and link weight promotes fairness," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    2. Wang, Chaoqian & Szolnoki, Attila, 2022. "Involution game with spatio-temporal heterogeneity of social resources," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    3. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    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. Wang, Qun & Wang, Hanchen & Zhang, Zhuxi & Li, Yumeng & Liu, Yu & Perc, Matjaž, 2018. "Heterogeneous investments promote cooperation in evolutionary public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 570-575.
    6. Chuanyun Li & Xia Cao & Ming Chi, 2020. "Research on an evolutionary game model and simulation of a cluster innovation network based on fairness preference," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    7. Yang, Han-Xin & Yang, Jing, 2019. "Reputation-based investment strategy promotes cooperation in public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 886-893.
    8. Fan, Ruguo & Zhang, Yingqing & Luo, Ming & Zhang, Hongjuan, 2017. "Promotion of cooperation induced by heterogeneity of both investment and payoff allocation in spatial public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 454-463.
    9. Wang, Hanchen & Sun, Yichun & Zheng, Lei & Du, Wenbo & Li, Yumeng, 2018. "The public goods game on scale-free networks with heterogeneous investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 396-404.
    10. Chen, Wei & Zhu, Qianlong & Wu, Te, 2023. "Unfairness promotes the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    11. Kurokawa, Shun, 2019. "How memory cost, switching cost, and payoff non-linearity affect the evolution of persistence," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 174-192.
    12. Yu, Fengyuan & Wang, Jianwei & Chen, Wei & He, Jialu, 2023. "Increased cooperation potential and risk under suppressed strategy differentiation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    13. Deng, Zhenghong & Huang, Yijie & Gu, Zhiyang & Deng, Zhilong & Xu, Jiwei, 2018. "The evolution of cooperation in spatial multigame with voluntary participation," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 41-46.
    14. Li, Yixiao & Shen, Bin, 2013. "The coevolution of partner switching and strategy updating in non-excludable public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4956-4965.

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