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The influence of age-driven investment on cooperation in spatial public goods games

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  • Tian, Lin-Lin
  • Li, Ming-Chu
  • Lu, Kun
  • Zhao, Xiao-Wei
  • Wang, Zhen

Abstract

In social and biological systems, the individual capacity of contribution usually varies during its lifespan. In this paper, we study the effect of age-driven investment on cooperation in the public goods game under quenched age (QueA), natural aging (NatA) and strategy aging (StrA) rules. By investigating the evolutionary dynamics and the spatial distribution on a square lattice, we find that cooperator clusters become more robust under the specific age structure, in which young cooperators usually locate on the margins. The StrA rule is the most effective at enhancing cooperation because the age characteristic helps the organization of cooperators defend against the invasion of defectors. The other rules require higher synergy factors for cooperation dominance where the old and young cooperators are well-mixed. In addition, the QueA rule improves cooperation by accelerating the extinction of defectors and the NatA rule performs the worst because the aging process breaks up the cooperative clusters. Our results may provide insight into the impact of age-dependent contributions on cooperative behaviors in real world situations.

Suggested Citation

  • Tian, Lin-Lin & Li, Ming-Chu & Lu, Kun & Zhao, Xiao-Wei & Wang, Zhen, 2013. "The influence of age-driven investment on cooperation in spatial public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 65-70.
    • Handle: RePEc:eee:chsofr:v:54:y:2013:i:c:p:65-70
    DOI: 10.1016/j.chaos.2013.05.017
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    3. Lv, Ran & Qian, Jia-Li & Hao, Qing-Yi & Wu, Chao-Yun & Guo, Ning & Ling, Xiang, 2023. "The impact of current and historical reputation with non-uniform change on cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. 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).
    5. Lu, Peng, 2015. "Individual choice and reputation distribution of cooperative behaviors among heterogeneous groups," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 39-46.
    6. Tian, Lin-Lin & Li, Ming-Chu & Wang, Zhen, 2016. "Cooperation enhanced by indirect reciprocity in spatial prisoner’s dilemma games for social P2P systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1252-1260.
    7. Wang, Mie & Kang, HongWei & Shen, Yong & Sun, XingPing & Chen, QingYi, 2021. "The role of alliance cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    8. Xia, Ke, 2021. "Average abundance function of multi-player threshold public goods without initial endowment evolutionary game model under differential aspiration levels and redistribution mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    9. Hong Ding & Lin Cao & Yizhi Ren & Kim-Kwang Raymond Choo & Benyun Shi, 2016. "Reputation-Based Investment Helps to Optimize Group Behaviors in Spatial Lattice Networks," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    10. Quan, Ji & Tang, Caixia & Zhou, Yawen & Wang, Xianjia & Yang, Jian-Bo, 2020. "Reputation evaluation with tolerance and reputation-dependent imitation on cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).

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