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Evolving cooperation in multichannel games

Author

Listed:
  • Kate Donahue

    (Cornell University)

  • Oliver P. Hauser

    (University of Exeter)

  • Martin A. Nowak

    (Harvard University
    Harvard University)

  • Christian Hilbe

    (Max Planck Institute for Evolutionary Biology)

Abstract

Humans routinely engage in many distinct interactions in parallel. Team members collaborate on several concurrent projects, and even whole nations interact with each other across a variety of issues, including trade, climate change and security. Yet the existing theory of direct reciprocity studies isolated repeated games. Such models cannot account for strategic attempts to use the vested interests in one game as a leverage to enforce cooperation in another. Here we introduce a general framework of multichannel games. Individuals interact with each other over multiple channels; each channel is a repeated game. Strategic choices in one channel can affect decisions in another. With analytical equilibrium calculations for the donation game and evolutionary simulations for several other games we show that such linkage facilitates cooperation. Our results suggest that previous studies tend to underestimate the human potential for reciprocity. When several interactions occur in parallel, people often learn to coordinate their behavior across games to maximize cooperation in each of them.

Suggested Citation

  • Kate Donahue & Oliver P. Hauser & Martin A. Nowak & Christian Hilbe, 2020. "Evolving cooperation in multichannel games," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17730-3
    DOI: 10.1038/s41467-020-17730-3
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    Citations

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    Cited by:

    1. Wu, Yu’e & Zhang, Zhipeng & Yang, Guoli & Liu, Haixin & Zhang, Qingfeng, 2022. "Evolution of cooperation driven by diversity on a double-layer square lattice," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    2. Wenman Chen & Ji Quan & Xianjia Wang, 2024. "The emergence and maintenance of cooperation in the public goods game under stochastic strategy updating rule with preference," Dynamic Games and Applications, Springer, vol. 14(5), pages 1225-1237, November.
    3. Quan, Ji & Chen, Xinyue & Wang, Xianjia, 2024. "Repeated prisoner's dilemma games in multi-player structured populations with crosstalk," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    4. Peter S. Park & Martin A. Nowak & Christian Hilbe, 2022. "Cooperation in alternating interactions with memory constraints," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    5. Cheng, Jiangjiang & Mei, Wenjun & Su, Wei & Chen, Ge, 2023. "Evolutionary games on networks: Phase transition, quasi-equilibrium, and mathematical principles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    6. Mo, Fei & Han, Wenchen, 2024. "Long homogeneous payoff records with the latest strategy promotes the cooperation," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    7. He, Jialu & Wang, Jianwei & Yu, Fengyuan & Chen, Wei & Xu, Wenshu, 2022. "The persistence and transition of multiple public goods games resolves the social dilemma," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    8. Li, Wen-Jing & Chen, Zhi & Jin, Ke-Zhong & Wang, Jun & Yuan, Lin & Gu, Changgui & Jiang, Luo-Luo & Perc, Matjaž, 2022. "Options for mobility and network reciprocity to jointly yield robust cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    9. Ma, Xiaojian & Quan, Ji & Wang, Xianjia, 2023. "Evolution of cooperation with nonlinear environment feedback in repeated public goods game," Applied Mathematics and Computation, Elsevier, vol. 452(C).

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