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Evolution of Cooperation in Social Dilemmas on Complex Networks

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  • Swami Iyer
  • Timothy Killingback

Abstract

Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner’s dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games.Author Summary: Social dilemmas embody the tension between individual self-interest on the one hand and the public good on the other that underlie many of the greatest challenges facing human and animal societies, such as the maintenance of altruism and the responsible use of common resources. Understanding the mechanisms through which cooperative, socially optimal, behavior can be established in social dilemmas is a fundamental problem in evolutionary biology and in many areas of the social sciences. Here we study how cooperative behavior can emerge in three key social dilemmas—known as the donation game, snowdrift game and sculling game—when interactions between individuals form a network. We show that in all three social dilemmas significantly higher levels of cooperative behavior typically emerge in such a situation as compared to what would be the case in the absence of any network structure. In particular, we show that certain structural properties that are common in real-world social networks have a significant effect in increasing the level of cooperative behavior that is present in all three social dilemmas.

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  • Swami Iyer & Timothy Killingback, 2016. "Evolution of Cooperation in Social Dilemmas on Complex Networks," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-25, February.
    • Handle: RePEc:plo:pcbi00:1004779
    DOI: 10.1371/journal.pcbi.1004779
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    Cited by:

    1. Deng, Wenfeng & Huang, Keke & Yang, Chunhua & Zhu, Hongqiu & Yu, Zhaofei, 2018. "Promote of cooperation in networked multiagent system based on fitness control," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 805-811.
    2. Bandyopadhyay, Abhirup & Kar, Samarjit, 2018. "Coevolution of cooperation and network structure in social dilemmas in evolutionary dynamic complex network," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 710-730.
    3. Swami Iyer & Timothy Killingback, 2020. "Evolution of Cooperation in Social Dilemmas with Assortative Interactions," Games, MDPI, vol. 11(4), pages 1-31, September.
    4. Marialisa Scatá & Barbara Attanasio & Aurelio La Corte, 2021. "Cognitive Profiling of Nodes in 6G through Multiplex Social Network and Evolutionary Collective Dynamics," Future Internet, MDPI, vol. 13(5), pages 1-17, May.
    5. Sarkar, Bijan, 2018. "Moran-evolution of cooperation: From well-mixed to heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 319-334.
    6. Sakiyama, Tomoko, 2021. "A power law network in an evolutionary hawk–dove game," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    7. Ke, Jianhong & Li, Ping-Ping & Lin, Zhenquan, 2022. "Dissatisfaction-driven replicator dynamics of the evolutionary snowdrift game in structured populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    8. Płatkowski, Tadeusz, 2022. "Cooperation in multi-person social dilemmas with other-regarding orientations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    9. Zhang, Xin-Jie & Tang, Yong & Xiong, Jason & Wang, Wei-Jia & Zhang, Yi-Cheng, 2020. "Ranking game on networks: The evolution of hierarchical society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    10. Guangming Ren & Lan Liu & Mingku Feng & Yingji He, 2018. "Coevolution of public goods game and networks based on survival of the fittest," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-11, September.
    11. Hendrik Richter, 2020. "Evolution of Cooperation for Multiple Mutant Configurations on All Regular Graphs with N ≤ 14 Players," Games, MDPI, vol. 11(1), pages 1-18, February.

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