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Evolutionary dynamics of group formation

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  • Marco Alberto Javarone
  • Daniele Marinazzo

Abstract

Group formation is a quite ubiquitous phenomenon across different animal species, whose individuals cluster together forming communities of diverse size. Previous investigations suggest that, in general, this phenomenon might have similar underlying reasons across the interested species, despite genetic and behavioral differences. For instance improving the individual safety (e.g. from predators), and increasing the probability to get food resources. Remarkably, the group size might strongly vary from species to species, e.g. shoals of fishes and herds of lions, and sometimes even within the same species, e.g. tribes and families in human societies. Here we build on previous theories stating that the dynamics of group formation may have evolutionary roots, and we explore this fascinating hypothesis from a purely theoretical perspective, with a model using the framework of Evolutionary Game Theory. In our model we hypothesize that homogeneity constitutes a fundamental ingredient in these dynamics. Accordingly, we study a population that tries to form homogeneous groups, i.e. composed of similar agents. The formation of a group can be interpreted as a strategy. Notably, agents can form a group (receiving a ‘group payoff’), or can act individually (receiving an ‘individual payoff’). The phase diagram of the modeled population shows a sharp transition between the ‘group phase’ and the ‘individual phase’, characterized by a critical ‘individual payoff’. Our results then support the hypothesis that the phenomenon of group formation has evolutionary roots.

Suggested Citation

  • Marco Alberto Javarone & Daniele Marinazzo, 2017. "Evolutionary dynamics of group formation," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-10, November.
  • Handle: RePEc:plo:pone00:0187960
    DOI: 10.1371/journal.pone.0187960
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    Citations

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    Cited by:

    1. Alexander G. Ginsberg & Feng Fu, 2018. "Evolution of Cooperation in Public Goods Games with Stochastic Opting-Out," Games, MDPI, vol. 10(1), pages 1-27, December.
    2. Sudakow, Ivan & Vakulenko, Sergey A., 2024. "New spin models in ecology: Super multi-stationarity and chaos," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    3. de Oliveira, B.F. & de Moraes, M.V. & Bazeia, D. & Szolnoki, A., 2021. "Mobility driven coexistence of living organisms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    4. Elad Shniderman & Yahav Avraham & Shir Shahal & Hamootal Duadi & Nir Davidson & Moti Fridman, 2024. "How synchronized human networks escape local minima," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    5. Flores, Lucas S. & Amaral, Marco A. & Vainstein, Mendeli H. & Fernandes, Heitor C.M., 2022. "Cooperation in regular lattices," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Yang, Zhengzhi & Zheng, Lei & Perc, Matjaž & Li, Yumeng, 2024. "Interaction state Q-learning promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 463(C).

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