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Evaluating fitness by integrating the highest payoff within the neighborhood promotes cooperation in social dilemmas

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  • Xia, Cheng-yi
  • Ma, Zhi-qin
  • Wang, Zhen
  • Wang, Juan

Abstract

In this paper, we propose a modified fitness evaluation mechanism, which integrates the environmental factors into the focal player’s fitness calculation, to investigate the evolution of cooperative behaviors in the prisoner’s dilemma game. Here, the fitness of a player is computed by combining the individual raw payoff and the highest payoff within the neighborhood, which is regulated by a single parameter termed as trust level η. We show, compared to the traditional version (η=0), that the cooperation level can be highly enhanced for η>0. Meanwhile, we illustrate the dynamical evolution of cooperators on the square lattice, and for different defection parameters b the FC−K curves are utilized to investigate the impact of noise during the strategy updates. Likely, the role of pursuing the highest payoff within the neighborhood also favors the survival of cooperators in the spatial snowdrift game. In addition, the sensibility of knowing the external factors is often not identical for all individuals and we consider the distributed trust level in which η is a distributed parameter, and the results indicate that pursuing the highest payoff in the neighborhood is also inspiring as a consequence of its positive effect on cooperation. The current results are highly instructive for us to further understand the maintenance and emergence of cooperation under the framework of evolutionary game theory.

Suggested Citation

  • Xia, Cheng-yi & Ma, Zhi-qin & Wang, Zhen & Wang, Juan, 2012. "Evaluating fitness by integrating the highest payoff within the neighborhood promotes cooperation in social dilemmas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6440-6447.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:24:p:6440-6447
    DOI: 10.1016/j.physa.2012.07.065
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    Citations

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    Cited by:

    1. Kohei Miyaji & Jun Tanimoto & Zhen Wang & Aya Hagishima & Naoki Ikegaya, 2013. "Direct Reciprocity in Spatial Populations Enhances R-Reciprocity As Well As ST-Reciprocity," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Li, Jiaqi & Zhang, Chunyan & Sun, Qinglin & Chen, Zengqiang, 2015. "Coevolution between strategy and social networks structure promotes cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 253-263.
    3. Cui, Guang-Hai & Li, Ming-Chu & Fan, Xin-Xin & Deonauth, Nakema & Wang, Zhen, 2014. "Optimism when winning and cautiousness when losing promote cooperation in the spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 181-189.
    4. Chen, Zhi-Gang & Wang, Tao & Xiao, De-Gui & Xu, Yin, 2013. "Can remembering history from predecessor promote cooperation in the next generation?," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 59-68.
    5. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    6. Wang, Yi-Ling, 2013. "Learning ability driven by majority selection enhances spatial reciprocity in prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 96-100.
    7. Tian, Lin-Lin & Li, Ming-Chu & Lu, Kun & Zhao, Xiao-Wei & Wang, Zhen, 2013. "The influence of age-driven investment on cooperation in spatial public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 65-70.
    8. Keizo Shigaki & Zhen Wang & Jun Tanimoto & Eriko Fukuda, 2013. "Effect of Initial Fraction of Cooperators on Cooperative Behavior in Evolutionary Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-7, November.
    9. Li, Hong-yang & Xiao, Jian & Li, Yu-meng & Wang, Zhen, 2013. "Effects of neighborhood type and size in spatial public goods game on diluted lattice," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 145-153.
    10. Han, Dun & Sun, Mei, 2014. "Can memory and conformism resolve the vaccination dilemma?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 95-104.
    11. Wang, Yi-Ling, 2013. "Asymmetric evaluation of fitness enhances spatial reciprocity in social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 76-81.
    12. Zhang, Yan, 2013. "The impact of other-regarding tendencies on the spatial vaccination game," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 209-215.
    13. Huang, Keke & Zheng, Xiaoping & Su, Yunpeng, 2015. "Effect of heterogeneous sub-populations on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 681-687.
    14. Wang, Zhen & Wu, Bin & Li, Ya-peng & Gao, Hang-xian & Li, Ming-chu, 2013. "Does coveting the performance of neighbors of thy neighbor enhance spatial reciprocity?," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 28-34.
    15. Yang, Ran & Chen, Tong & Chen, Qiao, 2018. "The impact of lotteries on cooperation in the public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 925-934.
    16. Guang Zhang & Nan He & Yanxia Dong, 2021. "A Proportional-Egalitarian Allocation Policy for Public Goods Problems with Complex Network," Mathematics, MDPI, vol. 9(17), pages 1-12, August.
    17. Sun, Xuemei & Zhang, Yiming & Ren, Xu & Chen, Ke, 2015. "Optimization deployment of wireless sensor networks based on culture–ant colony algorithm," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 58-70.
    18. Tanimoto, Jun, 2015. "The impact of initial cooperation fraction on the evolutionary fate in a spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 171-188.
    19. Zhang, Gui-Qing & Hu, Tao-Ping & Yu, Zi, 2016. "An improved fitness evaluation mechanism with noise in prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 276(C), pages 31-36.
    20. Zhang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Yan, Ming & Li, Yu, 2019. "Strategy preference promotes cooperation in spatial evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 181-188.
    21. Hu, Menglong & Wang, Juan & Kong, Lingcong & An, Kang & Bi, Tao & Guo, Baohong & Dong, Enzeng, 2015. "Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 47-52.
    22. Ding, Shuai & Wang, Juan & Ruan, Sumei & Xia, Chengyi, 2015. "Inferring to individual diversity promotes the cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 71(C), pages 91-99.
    23. Huang, Shasha & Luo, Dang, 2015. "Impact of separation of interaction and replacement neighborhoods on spatial reciprocity," Applied Mathematics and Computation, Elsevier, vol. 253(C), pages 318-323.

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