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A generalized public goods game with coupling of individual ability and project benefit

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  • Li-Xin Zhong
  • Wen-Juan Xu
  • Yun-Xin He
  • Chen-Yang Zhong
  • Rong-Da Chen
  • Tian Qiu
  • Yong-Dong Shi
  • Fei Ren

Abstract

Facing a heavy task, any single person can only make a limited contribution and team cooperation is needed. As one enjoys the benefit of the public goods, the potential benefits of the project are not always maximized and may be partly wasted. By incorporating individual ability and project benefit into the original public goods game, we study the coupling effect of the four parameters, the upper limit of individual contribution, the upper limit of individual benefit, the needed project cost and the upper limit of project benefit on the evolution of cooperation. Coevolving with the individual-level group size preferences, an increase in the upper limit of individual benefit promotes cooperation while an increase in the upper limit of individual contribution inhibits cooperation. The coupling of the upper limit of individual contribution and the needed project cost determines the critical point of the upper limit of project benefit, where the equilibrium frequency of cooperators reaches its highest level. Above the critical point, an increase in the upper limit of project benefit inhibits cooperation. The evolution of cooperation is closely related to the preferred group-size distribution. A functional relation between the frequency of cooperators and the dominant group size is found.

Suggested Citation

  • Li-Xin Zhong & Wen-Juan Xu & Yun-Xin He & Chen-Yang Zhong & Rong-Da Chen & Tian Qiu & Yong-Dong Shi & Fei Ren, 2017. "A generalized public goods game with coupling of individual ability and project benefit," Papers 1702.07423, arXiv.org, revised May 2017.
  • Handle: RePEc:arx:papers:1702.07423
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    References listed on IDEAS

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    1. Xu, C. & Ji, M. & Yap, Yee Jiun & Zheng, Da-Fang & Hui, P.M., 2011. "Costly punishment and cooperation in the evolutionary snowdrift game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(9), pages 1607-1614.
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    3. Frank Schweitzer & Laxmidar Behera, 2012. "Optimal Migration Promotes The Outbreak Of Cooperation In Heterogeneous Populations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-27.
    4. Shi, Yong-Dong & Zhong, Li-Xin & Xu, Wen-Juan, 2013. "Effects of group sensitivity on cooperation in N-person snowdrift game with dynamic grouping," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 132-138.
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    1. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & He, Yun-Xin & Qiu, Tian & Ren, Fei & Shi, Yong-Dong & Zhong, Chen-Yang, 2020. "Multiple learning mechanisms promote cooperation in public goods games with project selection," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).

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