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Research on the resilience of reputation mechanism to the cooperative environment in the face of external shocks

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  • Wang, Jiaoyuan
  • Yang, Yanlong

Abstract

Social development is changing rapidly, and the assumed stability of the cooperative environment is only an ideal state. In the majority of prior research concerning evolutionary games, it is commonly posited that external influences are absent, thereby allowing for an exclusive examination of the system’s intrinsic evolution. However, the situation in the real world is complex, dynamic, and unstable. Therefore, this paper proposes introducing an external shock that compels a change in the rate of cooperation during the evolutionary process. This approach aims to simulate environmental changes in the real world and to observe how these changes impact the rate of cooperation. When facing external shocks, the reputation mechanism has a certain degree of recovery ability, which provides certain support for the reputation theory. This paper also adds the mechanism of learning from historical strategies to the traditional reputation model, optimizing the resilience of the reputation mechanism in the face of external shocks. Simulation results show that history learning can promote the recovery of a cooperative environment faster and more stably, short memory length strengthens the role of temptation to defect, long memory amplifies the impact of the initial state, and the joint effect of history learning rate and memory length is complex.

Suggested Citation

  • Wang, Jiaoyuan & Yang, Yanlong, 2026. "Research on the resilience of reputation mechanism to the cooperative environment in the face of external shocks," Applied Mathematics and Computation, Elsevier, vol. 510(C).
  • Handle: RePEc:eee:apmaco:v:510:y:2026:i:c:s0096300325004394
    DOI: 10.1016/j.amc.2025.129713
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    References listed on IDEAS

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    1. Deng, Yunsheng & Zhang, Jihui, 2021. "Memory-based prisoner's dilemma game with history optimal strategy learning promotes cooperation on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    2. Haibo Chen & Zongjun Wang & Xuesong Yu & Qin Zhong, 2022. "Research on the Anti-Risk Mechanism of Mask Green Supply Chain from the Perspective of Cooperation between Retailers, Suppliers, and Financial Institutions," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    3. Ji, Jiezhou & Pan, Qiuhui & Zhu, Wenqiang & He, Mingfeng, 2023. "The influence of own historical information and environmental historical information on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    4. Zhang, Qianwei & Liu, Jiaqi & Zhang, Xinran, 2024. "Reputation-based disconnection-reconnection mechanism in Prisoner's Dilemma Game within dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 650(C).
    5. Chen, Xiaojie & Fu, Feng & Wang, Long, 2007. "Prisoner's Dilemma on community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 512-518.
    6. Li, Dandan & Sun, Xiaoxiao & He, Youxin & Han, Dun, 2022. "On prisoner’s dilemma game with psychological bias and memory learning," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    7. Wang, Jianwei & Wang, Rong & Yu, Fengyuan & Wang, Ziwei & Li, Qiaochu, 2020. "Learning continuous and consistent strategy promotes cooperation in prisoner’s dilemma game with mixed strategy," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    8. Zhen Wang & Lin Wang & Zi-Yu Yin & Cheng-Yi Xia, 2012. "Inferring Reputation Promotes the Evolution of Cooperation in Spatial Social Dilemma Games," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    9. Pan, Qiuhui & Wang, Yue & He, Mingfeng, 2022. "Impacts of special cooperation strategy with reward and punishment mechanism on cooperation evolution," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    10. Hanauske, Matthias & Kunz, Jennifer & Bernius, Steffen & König, Wolfgang, 2010. "Doves and hawks in economics revisited: An evolutionary quantum game theory based analysis of financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 5084-5102.
    11. Zhang, Huizhen & An, Tianbo & Yan, Pingping & Hu, Kaipeng & An, Jinjin & Shi, Lijuan & Zhao, Jian & Wang, Jingrui, 2024. "Exploring cooperative evolution with tunable payoff’s loners using reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    12. Shiguang Hu & Le Ru & Bo Lu & Zhenhua Wang & Wenfei Wang & Hailong Xi, 2024. "Stochastic Evolutionary Analysis of an Aerial Attack–Defense Game in Uncertain Environments," Mathematics, MDPI, vol. 12(19), pages 1-22, September.
    13. Li, Dandan & Zhou, Kai & Sun, Mei & Han, Dun, 2023. "Investigating the effectiveness of individuals’ historical memory for the evolution of the prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    14. Wang, Xiaofeng & Chen, Xiaojie & Gao, Jia & Wang, Long, 2013. "Reputation-based mutual selection rule promotes cooperation in spatial threshold public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 181-187.
    15. Xiaojie Chen & Alana Schick & Michael Doebeli & Alistair Blachford & Long Wang, 2012. "Reputation-Based Conditional Interaction Supports Cooperation in Well-Mixed Prisoner’s Dilemmas," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-7, May.
    16. Zhu, Peican & Wang, Xiaoyu & Jia, Danyang & Guo, Yangming & Li, Shudong & Chu, Chen, 2020. "Investigating the co-evolution of node reputation and edge-strategy in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    17. Chu, Chen & Zhai, Yao & Mu, Chunjiang & Hu, Die & Li, Tong & Shi, Lei, 2019. "Reputation-based popularity promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    18. Bi, Yan & Yang, Hui, 2023. "Based on reputation consistent strategy times promotes cooperation in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    19. Lin, Jiaying & Long, Pinduo & Liang, Jinfeng & Dai, Qionglin & Li, Haihong & Yang, Junzhong, 2025. "The coevolution of cooperation: Integrating Q-learning and occasional social interactions in evolutionary games," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    20. Becchetti, Leonardo & Ciciretti, Rocco & Paolantonio, Adriana, 2016. "The cooperative bank difference before and after the global financial crisis," Journal of International Money and Finance, Elsevier, vol. 69(C), pages 224-246.
    21. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
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