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Adaptive and Bounded Investment Returns Promote Cooperation in Spatial Public Goods Games

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  • Xiaojie Chen
  • Yongkui Liu
  • Yonghui Zhou
  • Long Wang
  • Matjaž Perc

Abstract

The public goods game is one of the most famous models for studying the evolution of cooperation in sizable groups. The multiplication factor in this game can characterize the investment return from the public good, which may be variable depending on the interactive environment in realistic situations. Instead of using the same universal value, here we consider that the multiplication factor in each group is updated based on the differences between the local and global interactive environments in the spatial public goods game, but meanwhile limited to within a certain range. We find that the adaptive and bounded investment returns can significantly promote cooperation. In particular, full cooperation can be achieved for high feedback strength when appropriate limitation is set for the investment return. Also, we show that the fraction of cooperators in the whole population can become larger if the lower and upper limits of the multiplication factor are increased. Furthermore, in comparison to the traditionally spatial public goods game where the multiplication factor in each group is identical and fixed, we find that cooperation can be better promoted if the multiplication factor is constrained to adjust between one and the group size in our model. Our results highlight the importance of the locally adaptive and bounded investment returns for the emergence and dominance of cooperative behavior in structured populations.

Suggested Citation

  • Xiaojie Chen & Yongkui Liu & Yonghui Zhou & Long Wang & Matjaž Perc, 2012. "Adaptive and Bounded Investment Returns Promote Cooperation in Spatial Public Goods Games," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.
  • Handle: RePEc:plo:pone00:0036895
    DOI: 10.1371/journal.pone.0036895
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    References listed on IDEAS

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    Cited by:

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    2. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    3. Chengzhang Ma & Wei Cao & Wangheng Liu & Rong Gui & Ya Jia, 2013. "Direct Sum Matrix Game with Prisoner's Dilemma and Snowdrift Game," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-7, December.
    4. Pan, Jianchen & Zhang, Lan & Han, Wenchen & Huang, Changwei, 2023. "Heterogeneous investment promotes cooperation in spatial public goods game on hypergraphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    5. Li, Jing & Wang, Jiang, 2018. "Locality based wealth rule favors cooperation in costly public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 1-7.
    6. Wang, Qun & Wang, Hanchen & Zhang, Zhuxi & Li, Yumeng & Liu, Yu & Perc, Matjaž, 2018. "Heterogeneous investments promote cooperation in evolutionary public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 570-575.
    7. Ma, Xiaojian & Quan, Ji & Wang, Xianjia, 2021. "Effect of reputation-based heterogeneous investment on cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    8. Liu, Yandi & Zheng, Tainian & Li, Yonghui & Dai, Yu, 2020. "Does the conformity save us when information advantage fails?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    9. Schauf, Andrew & Oh, Poong, 2021. "Adaptation strategies and collective dynamics of extraction in networked commons of bistable resources," SocArXiv wmtqk, Center for Open Science.
    10. McAvoy, Alex & Fraiman, Nicolas & Hauert, Christoph & Wakeley, John & Nowak, Martin A., 2018. "Public goods games in populations with fluctuating size," Theoretical Population Biology, Elsevier, vol. 121(C), pages 72-84.
    11. Quan, Ji & Dong, Xu & Wang, Xianjia, 2022. "Rational conformity behavior in social learning promotes cooperation in spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    12. Fan, Ruguo & Zhang, Yingqing & Luo, Ming & Zhang, Hongjuan, 2017. "Promotion of cooperation induced by heterogeneity of both investment and payoff allocation in spatial public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 454-463.
    13. Wang, Hanchen & Sun, Yichun & Zheng, Lei & Du, Wenbo & Li, Yumeng, 2018. "The public goods game on scale-free networks with heterogeneous investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 396-404.
    14. Li, Pei & Duan, Haibin, 2015. "Evolution of cooperation driven by incremental learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 14-22.
    15. 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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