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Aspiration drives adaptive switching between two different payoff matrices

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  • Li, Jiaqi
  • Zhang, Jianlei
  • Chen, Zengqiang
  • Liu, Qun

Abstract

Under given social dilemma, different individuals perhaps have different perceptions for the dilemma intensity. Generally speaking, the degree of individual’s perception should be closely related to its ability, the stronger the ability of individual, the weaker the perception for the dilemma intensity will be. On the other hand, the competent individuals may be more likely to carry out altruistic cooperation behavior than those who are relatively lacking in ability. Considering these facts, we introduce an evolutionary game model in which individual can adaptively switch between two payoff matrices with different temptations based on aspiration to explore the cooperation dynamics in spatial prisoner’s dilemma. In this model, two different payoff matrices are denoted by Mw and Ms respectively, the temptation value of the former is small, and the one of the latter is large. For the individual who has adopted Mw to interact, the higher the individual is satisfied with the current payoff, the lower the probability of switching to Ms in the next round, while for the individual who has adopted Ms to interact, the higher the individual is satisfied with the current payoff, the higher the probability of switching to Mw in the next round. Experimental results show that this mechanism of adaptive switching between payoff matrices with different temptations can effectively promote the cooperation of spatial prisoner’s dilemma, and the appropriate aspiration level of individual can provide the most favorable environment for the diffusion of cooperation. The difference in the perception for dilemma intensity will be a new perspective in the study of networked evolution game.

Suggested Citation

  • Li, Jiaqi & Zhang, Jianlei & Chen, Zengqiang & Liu, Qun, 2023. "Aspiration drives adaptive switching between two different payoff matrices," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    • Handle: RePEc:eee:apmaco:v:446:y:2023:i:c:s0096300323000504
    DOI: 10.1016/j.amc.2023.127881
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    1. Li, Zhibin & Jia, Danyang & Guo, Hao & Geng, Yini & Shen, Chen & Wang, Zhen & Li, Xuelong, 2019. "The effect of multigame on cooperation in spatial network," Applied Mathematics and Computation, Elsevier, vol. 351(C), pages 162-167.
    2. Jianlei Zhang & Zimin Xu & Zengqiang Chen, 2018. "Effects of strategy switching and network topology on decision-making in multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(9), pages 1934-1949, July.
    3. 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.
    4. Liu, Chen & Shi, Juan & Li, Tong & Liu, Jinzhuo, 2019. "Aspiration driven coevolution resolves social dilemmas in networks," Applied Mathematics and Computation, Elsevier, vol. 342(C), pages 247-254.
    5. EL-Seidy, Essam, 2015. "The effect of noise and average relatedness between players in iterated games," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 343-350.
    6. Ye, Wenxing & Feng, Weiying & Lü, Chen & Fan, Suohai, 2017. "Memory-based prisoner’s dilemma game with conditional selection on networks," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 31-37.
    7. Jian, Qing & Li, Xiaopeng & Wang, Juan & Xia, Chengyi, 2021. "Impact of reputation assortment on tag-mediated altruistic behaviors in the spatial lattice," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    8. K. M. Ariful Kabir & Jun Tanimoto & Zhen Wang, 2018. "Influence of bolstering network reciprocity in the evolutionary spatial Prisoner’s Dilemma game: a perspective," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(12), pages 1-10, December.
    9. 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.
    10. Chen, Yahong & Huang, He, 2022. "Modeling the impacts of contact tracing on an epidemic with asymptomatic infection," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    11. Guo, Tian & Guo, Mi & Zhang, Yan & Liang, Shuanglu, 2019. "The effect of aspiration on the evolution of cooperation in spatial multigame," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 27-32.
    12. Li, Jiaqi & Dang, Jianwu & Zhang, Jianlei, 2020. "Length of information-based bidirectional choice in spatial prisoner’s dilemma," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    13. Zeng, Ziyan & Li, Yuhan & Feng, Minyu, 2022. "The spatial inheritance enhances cooperation in weak prisoner’s dilemmas with agents’ exponential lifespan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    14. Liu, Jinzhuo & Meng, Haoran & Wang, Wei & Li, Tong & Yu, Yong, 2018. "Synergy punishment promotes cooperation in spatial public good game," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 214-218.
    15. Li, Yan & Ye, Hang & Zhang, Hong, 2016. "Evolution of cooperation driven by social-welfare-based migration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 48-56.
    16. Ye, Wenxing & Fan, Suohai, 2017. "Evolutionary snowdrift game with rational selection based on radical evaluation," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 310-317.
    17. Luo, Chao & Zhang, Xiaolin & Liu, Hong & Shao, Rui, 2016. "Cooperation in memory-based prisoner’s dilemma game on interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 560-569.
    18. Li, Minlan & Liu, Yan-Ping & Han, Yanyan & Wang, Rui-Wu, 2022. "Environmental heterogeneity unifies the effect of spatial structure on the altruistic cooperation in game-theory paradigms," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    19. Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.
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