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Generosity in public goods game with the aspiration-driven rule

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  • Lv, Shaojie
  • Zhao, Changheng
  • Li, Jiaying

Abstract

In nature and society, individuals cannot perceive their environment and make choices without errors. These error-driven perceptual and decision making processes can result in unintended defective behaviors that undermine reciprocity. However, generosity can promote cooperation by tolerating unintended defection. Meanwhile, widespread self-learning phenomena such as aspiration-driven behaviors do not require external information, thereby avoiding the perception errors when obtaining information from others. Therefore, a Markov process combining generosity and aspiration-driven behaviors is proposed in the present study. For weak intensity of aspiration ω, the closed-form expression for the average abundance of cooperators is derived. We also investigate the case of strong ω by numerical analysis. The results show that the average abundance of cooperators decreases with the increase of ω for low aspiration level. For high aspiration levels, the average abundance of cooperation is a non-monotonic function of ω. The generosity is thus conducive to the evolution of cooperation. Under strong intensity of aspiration ω, the generosity can significantly promote cooperation when aspiration levels are high.

Suggested Citation

  • Lv, Shaojie & Zhao, Changheng & Li, Jiaying, 2022. "Generosity in public goods game with the aspiration-driven rule," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    • Handle: RePEc:eee:chsofr:v:165:y:2022:i:p2:s0960077922010153
    DOI: 10.1016/j.chaos.2022.112836
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    References listed on IDEAS

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    Cited by:

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    2. Kang, Hongwei & Li, Zhekang & Shen, Yong & Huang, Zhiyuan & Sun, Xingping & Chen, Qingyi, 2024. "From eligibility to suitability: Regulation and restriction of reputation-based access system on free-riding behavior in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).

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