Extended average abundance function of multi-player snowdrift evolutionary game under aspiration driven rule
WANG Xianjia1,2, XIA Ke1
1. School of Economics and Management, Wuhan University, Wuhan 430072, China; 2. Institute of Systems Engineering, Wuhan University, Wuhan 430072, China
Abstract：With further study of game theory, evolutionary game model has been widely used in the analysis of many social phenomena and economic problems. In evolutionary game model, strategy updating rule is introduced into the state transition equation, and the corresponding Markov chain is obtained to study the evolutionary state of population. When the Markov chain has no absorbing states, the average abundance function is used to study the evolutionary state of population. The extended average abundance function is derived by analyzing the stationary distribution of Markov chain using aspiration driven rule in the strategy updating rules. At the same time, by applying the multi-player evolutionary game model to snowdrift evolutionary game, extended average abundance function of multi-player snowdrift evolutionary game model is obtained. By means of numerical analysis, the influence of corresponding parameters on the average abundance function is calculated and analyzed, and how the variation of parameters affects the behavior of enterprises in the game is studied with a specific case. The research shows that the proportion of cooperators will be increased by changing relevant parameters, and this conclusion points out the direction for how to regulate the corresponding parameters to promote cooperation in practical application.
王先甲, 夏可. 多人雪堆演化博弈在愿景驱动规则下的扩展平均丰度函数[J]. 系统工程理论与实践, 2019, 39(5): 1128-1136.
WANG Xianjia, XIA Ke. Extended average abundance function of multi-player snowdrift evolutionary game under aspiration driven rule. Systems Engineering - Theory & Practice, 2019, 39(5): 1128-1136.
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2019, Vol. 39 
