Evolutionary game on a stochastic growth network

Gang Li, Xiao-Gang Jin and Zhi-Huan Song

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 24, 6664-6673

Abstract: In some real complex systems the structures are difficult to map or changing over time. To explore the evolution of strategies on these complex systems, it is not realistic enough to specify their structures or topological properties in advance. In this paper, we address the evolutionary game on a stochastic growth network adopting the prisoner’s dilemma game. We introduce a growing rate q to control the ratio of network growth to strategy evolution. A large q denotes that the network grows faster than strategy evolution. Simulation results show that a fast growing rate is helpful to promote the average payoffs of both cooperators and defectors. Moreover, this parameter also significantly influences the cooperation frequency on the resulting networks. The coexisting mechanisms in this paper may provide a beneficial insight for understanding the emergence of complex topological structures and game behaviors in numerous real systems.

Keywords: Stochastic growth model; Evolutionary game; Prisoner’s dilemma game; Topological property; Game behavior (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:24:p:6664-6673

DOI: 10.1016/j.physa.2012.07.057

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