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Evolutionary multigame with conformists and profiteers based on dynamic complex networks

Urheber*innen

Pi,  Bin
External Organizations;

Zeng,  Ziyan
External Organizations;

Feng,  Minyu
External Organizations;

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

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Zitation

Pi, B., Zeng, Z., Feng, M., Kurths, J. (2022): Evolutionary multigame with conformists and profiteers based on dynamic complex networks. - Chaos, 32, 2, 023117.
https://doi.org/10.1063/5.0081954


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_27042
Zusammenfassung
Evolutionary game on complex networks provides a new research framework for analyzing and predicting group decision-making behavior in an interactive environment, in which most researchers assumed players as profiteers. However, current studies have shown that players are sometimes conformists rather than profit-seeking in society, but most research has been discussed on a simple game without considering the impact of multiple games. In this paper, we study the influence of conformists and profiteers on the evolution of cooperation in multiple games and illustrate two different strategy-updating rules based on these conformists and profiteers. Different from previous studies, we introduce a similarity between players into strategy-updating rules and explore the evolutionary game process, including the strategy updating, the transformation of players’ type, and the dynamic evolution of the network structure. In the simulation, we implement our model on scale-free and regular networks and provide some explanations from the perspective of strategy transition, type transition, and network topology properties to prove the validity of our model. The study of network evolutionary games can provide a new perspective for explaining cooperation in society. Our task is to incorporate conformists and multigames into the traditional evolutionary game, which are more consistent with reality. Based on this model, this paper proposes two different strategy-updating rules and investigates their impact on the evolution of cooperation in the network. In addition, we make an interpretation of the simulation results in terms of strategy transition, type transition, and network topology properties. Our work may shed some new light on the study of network evolutionary games with conformists and multigames.