Extortion evolutionary game on scale-free networks with tunable clustering

Aizhong Shen, Zili Gao, Dan Cui and Chen Gu

Physica A: Statistical Mechanics and its Applications, 2024, vol. 637, issue C

Abstract: In this paper, we study the evolution of extortion with cooperation and defection strategies on scale-free networks with a tunable value of clustering under the normalized payoff framework. We investigate the influence of the clustering coefficient on cooperation behaviors based on the Prisoner’s Dilemma game with a single parameter. We simulate the evolution of cooperation with different extortion factors. For the smaller value of extortion factor, the result shows that the higher clustering coefficient is conducive to the spread of cooperation behaviors among small-degree and middle-degree nodes, which can maintain cooperation behaviors on the networks. However, for the larger value of extortion factor, the lower clustering coefficient can support cooperators invade into defectors and extortioners for all nodes. In addition, extortion strategies can act as catalysts to promote the frequencies of cooperation compared to the two-strategy game. These results are more significant for the smaller value of the benefit factor. Moreover, there exists an optimal value of the extortion factor to promote cooperation behaviors for different clustering coefficients.

Keywords: Cooperation behavior; Extortion evolution; Zero determinant strategy; Clustering coefficients (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:637:y:2024:i:c:s0378437124000761

DOI: 10.1016/j.physa.2024.129568

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