中国物理B ›› 2024, Vol. 33 ›› Issue (9): 90204-090204.doi: 10.1088/1674-1056/ad5aee

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Effect of distribution of fines on evolution of cooperation in spatial public goods game

Xing-Ping Sun(孙兴平), Yan-Zheng Bi(毕研政), Hong-Wei Kang(康洪炜)†, Yong Shen(沈勇), and Qing-Yi Chen(陈清毅)   

  1. School of Software, Yunnan University, Kunming 650000, China
  • 收稿日期:2024-04-22 修回日期:2024-05-26 接受日期:2024-06-24 发布日期:2024-08-15
  • 通讯作者: Hong-Wei Kang E-mail:hwkang@ynu.edu.cn
  • 基金资助:
    Project supported by the Open Foundation of Key Laboratory of Software Engineering of Yunnan Province (Grant Nos. 2020SE308 and 2020SE309).

Effect of distribution of fines on evolution of cooperation in spatial public goods game

Xing-Ping Sun(孙兴平), Yan-Zheng Bi(毕研政), Hong-Wei Kang(康洪炜)†, Yong Shen(沈勇), and Qing-Yi Chen(陈清毅)   

  1. School of Software, Yunnan University, Kunming 650000, China
  • Received:2024-04-22 Revised:2024-05-26 Accepted:2024-06-24 Published:2024-08-15
  • Contact: Hong-Wei Kang E-mail:hwkang@ynu.edu.cn
  • Supported by:
    Project supported by the Open Foundation of Key Laboratory of Software Engineering of Yunnan Province (Grant Nos. 2020SE308 and 2020SE309).

摘要: In the realm of public goods game, punishment, as a potent tool, stands out for fostering cooperation. While it effectively addresses the first-order free-rider problem, the associated costs can be substantial. Punishers incur expenses in imposing sanctions, while defectors face fines. Unfortunately, these monetary elements seemingly vanish into thin air, representing a loss to the system itself. However, by virtue of the redistribution of fines to cooperators and punishers, not only can we mitigate this loss, but the rewards for these cooperative individuals can be enhanced. Based upon this premise, this paper introduces a fine distribution mechanism to the traditional pool punishment model. Under identical parameter settings, by conducting a comparative experiment with the conventional punishment model, the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game. The experimental results clearly demonstrate that, in instances where the punishment cost is prohibitively high, the cooperative strategies of the traditional pool punishment model may completely collapse. However, the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies, thus highlighting its effectiveness in promoting and preserving cooperation, even in the face of substantial punishment cost.

关键词: public goods game, fine distribution, cooperation

Abstract: In the realm of public goods game, punishment, as a potent tool, stands out for fostering cooperation. While it effectively addresses the first-order free-rider problem, the associated costs can be substantial. Punishers incur expenses in imposing sanctions, while defectors face fines. Unfortunately, these monetary elements seemingly vanish into thin air, representing a loss to the system itself. However, by virtue of the redistribution of fines to cooperators and punishers, not only can we mitigate this loss, but the rewards for these cooperative individuals can be enhanced. Based upon this premise, this paper introduces a fine distribution mechanism to the traditional pool punishment model. Under identical parameter settings, by conducting a comparative experiment with the conventional punishment model, the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game. The experimental results clearly demonstrate that, in instances where the punishment cost is prohibitively high, the cooperative strategies of the traditional pool punishment model may completely collapse. However, the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies, thus highlighting its effectiveness in promoting and preserving cooperation, even in the face of substantial punishment cost.

Key words: public goods game, fine distribution, cooperation

中图分类号:  (Decision theory and game theory)

  • 02.50.Le
02.50.Ng (Distribution theory and Monte Carlo studies) 02.60.Cb (Numerical simulation; solution of equations) 02.70.Uu (Applications of Monte Carlo methods)