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Evolutionary dynamics of trust in the N-player trust game with individual reward and punishment

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  • Xing Fang

    (University of Electronic Science and Technology of China)

  • Xiaojie Chen

    (University of Electronic Science and Technology of China)

Abstract

Trust plays an important role in human society. However, how does trust evolve is a huge challenge. The trust game is a well-known paradigm to measure the evolution of trust in a population. Reward and punishment as the common types of incentives can be used to improve the trustworthiness. However, it remains unclear how reward and punishment actually influence the evolutionary dynamics of trust. Here, we introduce individual reward and punishment into the N-player trust game model in an infinite well-mixed population, where investors use a part of the returned fund to reward trustworthy trustees and meanwhile punish untrustworthy trustees. We then investigate the evolutionary dynamics of trust by means of replicator equations. We show that the introduction of reward and punishment can lead to the stable coexistence state of investors and trustworthy trustees, which indicates that the evolution of trust can be greatly promoted. We reveal that the attraction domain of the coexistence state becomes larger as investors increase the incentive strength from the returned fund for reward and punishment. In addition, we find that the increase of the reward coefficient can enlarge the attraction domain of the coexistence state, which implies that reward can better promote the evolution of trust than punishment.

Suggested Citation

  • Xing Fang & Xiaojie Chen, 2021. "Evolutionary dynamics of trust in the N-player trust game with individual reward and punishment," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(9), pages 1-7, September.
    • Handle: RePEc:spr:eurphb:v:94:y:2021:i:9:d:10.1140_epjb_s10051-021-00185-w
    DOI: 10.1140/epjb/s10051-021-00185-w
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    Cited by:

    1. Guo, Ruqiang & Liu, Linjie & Liu, Yuyuan & Zhang, Liang, 2023. "Evolution of trust in a hierarchical population with different investors based on investment behavioral theory," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    2. Sun, Ketian & Liu, Yang & Chen, Xiaojie & Szolnoki, Attila, 2022. "Evolution of trust in a hierarchical population with punishing investors," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    3. Liu, Yuyuan & Liu, Linjie & Guo, Ruqiang & Zhang, Liang, 2023. "N-player repeated evolutionary trust game under government management," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. Gao, Meng & Li, Zhi & Wu, Te, 2023. "Evolutionary dynamics of friendship-driven reputation strategies," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    5. Guo, Ruqiang & Liu, Linjie & Liu, Yuyuan & Zhang, Liang, 2024. "Evolution of trust in the N-player trust game with the margin system," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    6. Wang, Chaoqian, 2024. "Evolution of trust in structured populations," Applied Mathematics and Computation, Elsevier, vol. 471(C).

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