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Reward depending on public funds stimulates cooperation in spatial prisoner’s dilemma games

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  • Li, Ya
  • Chen, Shanxiong
  • Niu, Ben

Abstract

Prisoner’s dilemma (shortly, PD) games are studied on a square lattice, in which reward mechanisms are considered to stimulate cooperation. It is known to all that results vary with different reward methods. The tax mechanism, an effective tool to adjust the economy, inspires a reward approach where each player should pay corresponding taxes according to their payoff ranks to gather public funds, which is utilized to reward cooperators. There are three main reward levels: high intensity, middle intensity and low intensity. When total public funds keep relatively stable, the reward coverage is determined by the reward intensity. In other words, high intensity of reward is accompanied with narrow range and low intensity accompanies with wide range. Through the proposed model, whether the new reward mechanism can stimulate cooperation and what reward level is the optimum choice could be studied. Simulations reveal that this new mechanism is of great benefit to cooperation and it is noteworthy that low reward intensity with wide coverage has the biggest impact on cooperation.

Suggested Citation

  • Li, Ya & Chen, Shanxiong & Niu, Ben, 2018. "Reward depending on public funds stimulates cooperation in spatial prisoner’s dilemma games," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 38-45.
  • Handle: RePEc:eee:chsofr:v:114:y:2018:i:c:p:38-45
    DOI: 10.1016/j.chaos.2018.07.002
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    as
    1. Xuelong Li & Marko Jusup & Zhen Wang & Huijia Li & Lei Shi & Boris Podobnik & H. Eugene Stanley & Shlomo Havlin & Stefano Boccaletti, 2018. "Punishment diminishes the benefits of network reciprocity in social dilemma experiments," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(1), pages 30-35, January.
    2. Benjamin Allen & Gabor Lippner & Yu-Ting Chen & Babak Fotouhi & Naghmeh Momeni & Shing-Tung Yau & Martin A. Nowak, 2017. "Evolutionary dynamics on any population structure," Nature, Nature, vol. 544(7649), pages 227-230, April.
    3. Falk, Armin & Fischbacher, Urs, 2006. "A theory of reciprocity," Games and Economic Behavior, Elsevier, vol. 54(2), pages 293-315, February.
    4. Li, Ya & Lan, Xin & Deng, Xinyang & Sadiq, Rehan & Deng, Yong, 2014. "Comprehensive consideration of strategy updating promotes cooperation in the prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 284-292.
    5. Erez Lieberman & Christoph Hauert & Martin A. Nowak, 2005. "Evolutionary dynamics on graphs," Nature, Nature, vol. 433(7023), pages 312-316, January.
    6. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    7. 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.
    8. Rick L. Riolo & Michael D. Cohen & Robert Axelrod, 2001. "Evolution of cooperation without reciprocity," Nature, Nature, vol. 414(6862), pages 441-443, November.
    9. Gary E Bolton & Axel Ockenfels, 1997. "A Theory of Equity, Reciprocity, and Competition," Levine's Working Paper Archive 1889, David K. Levine.
    10. Li, Dandan & Ma, Jing & Tian, Zihao & Zhu, Hengmin, 2015. "An evolutionary game for the diffusion of rumor in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 51-58.
    11. Geng, Yini & Shen, Chen & Hu, Kaipeng & Shi, Lei, 2018. "Impact of punishment on the evolution of cooperation in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 540-545.
    12. Christoph Hauert & Michael Doebeli, 2004. "Spatial structure often inhibits the evolution of cooperation in the snowdrift game," Nature, Nature, vol. 428(6983), pages 643-646, April.
    13. Xiuling Wang & Jie Wu & Gang Shu & Ya Li, 2014. "Punishment Based on Public Benefit Fund Significantly Promotes Cooperation," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-8, August.
    14. Jeff Gore & Hyun Youk & Alexander van Oudenaarden, 2009. "Snowdrift game dynamics and facultative cheating in yeast," Nature, Nature, vol. 459(7244), pages 253-256, May.
    15. Benjamin Grant Purzycki & Coren Apicella & Quentin D. Atkinson & Emma Cohen & Rita Anne McNamara & Aiyana K. Willard & Dimitris Xygalatas & Ara Norenzayan & Joseph Henrich, 2016. "Moralistic gods, supernatural punishment and the expansion of human sociality," Nature, Nature, vol. 530(7590), pages 327-330, February.
    16. Zhenhua Pei & Baokui Wang & Jinming Du, 2016. "Effects of income redistribution on the evolution of cooperation in spatial public goods games," Papers 1611.01531, arXiv.org.
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    8. Alfaro, Gaspar & Sanjuan, Miguel A.F., 2022. "Time-dependent effects hinder cooperation on the public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    9. Pu, Jia & Jia, Tao & Li, Ya, 2019. "Effects of time cost on the evolution of cooperation in snowdrift game," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 146-151.
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