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Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

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  • Jorge Peña
  • Yannick Rochat

Abstract

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.

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  • Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    • Handle: RePEc:plo:pone00:0044514
    DOI: 10.1371/journal.pone.0044514
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    Cited by:

    1. Marco Tomassini & Alberto Antonioni, 2019. "Computational Behavioral Models for Public Goods Games on Social Networks," Games, MDPI, vol. 10(3), pages 1-14, September.
    2. Stojkoski, Viktor & Karbevski, Marko & Utkovski, Zoran & Basnarkov, Lasko & Kocarev, Ljupco, 2021. "Evolution of cooperation in networked heterogeneous fluctuating environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    3. Pilwon Kim, 2017. "Evolution of Cooperation through Power Law Distributed Conflicts," Complexity, Hindawi, vol. 2017, pages 1-7, January.
    4. D. Timothy Bishop & Mark Broom & Richard Southwell, 2020. "Chris Cannings: A Life in Games," Dynamic Games and Applications, Springer, vol. 10(3), pages 591-617, September.
    5. Chen, Wei & Yang, Zhihu & Wu, Te, 2021. "Evolution of cooperation driven by collective interdependence on multilayer networks," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    6. Zhang, Wei & Brandes, Ulrik, 2023. "Is cooperation sustained under increased mixing in evolutionary public goods games on networks?," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    7. Jorge Peña & Bin Wu & Jordi Arranz & Arne Traulsen, 2016. "Evolutionary Games of Multiplayer Cooperation on Graphs," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-15, August.

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