Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs

doi:10.1007/s11467-017-0698-2

Front. Phys.

2018, Vol. 13

Issue (1) : 130201 https://doi.org/10.1007/s11467-017-0698-2

RESEARCH ARTICLE

Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs

Li-Min Ying¹, Jie Zhou¹, Ming Tang², Shu-Guang Guan¹, Yong Zou¹(

)

¹. Department of Physics, East China Normal University, Shanghai 200062, China
². School of Information Science Technology, East China Normal University, Shanghai 200241, China

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Abstract

The mean fixation time is often not accurate for describing the timescales of fixation probabilities of evolutionary games taking place on complex networks. We simulate the game dynamics on top of complex network topologies and approximate the fixation time distributions using a mean-field approach. We assume that there are two absorbing states. Numerically, we show that the mean fixation time is sufficient in characterizing the evolutionary timescales when network structures are close to the well-mixing condition. In contrast, the mean fixation time shows large inaccuracies when networks become sparse. The approximation accuracy is determined by the network structure, and hence by the suitability of the mean-field approach. The numerical results show good agreement with the theoretical predictions.

Keywords fixation time distribution complex networks coordination game

Corresponding Author(s): Yong Zou

Issue Date: 28 August 2017

Cite this article:

Li-Min Ying,Jie Zhou,Ming Tang, et al. Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs[J]. Front. Phys. , 2018, 13(1): 130201.

URL:

https://academic.hep.com.cn/fop/EN/10.1007/s11467-017-0698-2
https://academic.hep.com.cn/fop/EN/Y2018/V13/I1/130201

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