Evolutionary Self-Questioning Games with Local Contribution
LIU Yong-Kui1, LI Zhi1, CHEN Xiao-Jie2,3, WANG Long 1,2
1Center for Complex Systems, Department of Automatic Control Engineering, Xidian University, Xi'an 7100712State Key Laboratory for Turbulence and Complex Systems, Center for Systems and Control, College of Engineering, Peking University, Beijing 1008713Department of Zoology, University of British Columbia, Vancouver BC V6T 1Z4, Canada
Evolutionary Self-Questioning Games with Local Contribution
LIU Yong-Kui1, LI Zhi1, CHEN Xiao-Jie2,3, WANG Long 1,2
1Center for Complex Systems, Department of Automatic Control Engineering, Xidian University, Xi'an 7100712State Key Laboratory for Turbulence and Complex Systems, Center for Systems and Control, College of Engineering, Peking University, Beijing 1008713Department of Zoology, University of British Columbia, Vancouver BC V6T 1Z4, Canada
摘要We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their strategies by self-questioning. An individual with introspection can determine whether its current strategy is superior by playing a virtual round of the game and its local contribution is defined as the sum of all the payoffs its neighbors collect against it. In our model, the performance of an individual is determined by both its payoff and local contribution through a linear combination. We demonstrate that the present mechanism can produce very robust cooperative behavior in both games. Furthermore, we provide theoretical analysis based on mean-field approximation, and find that the analytical predictions are qualitatively consistent with the simulation results.
Abstract：We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their strategies by self-questioning. An individual with introspection can determine whether its current strategy is superior by playing a virtual round of the game and its local contribution is defined as the sum of all the payoffs its neighbors collect against it. In our model, the performance of an individual is determined by both its payoff and local contribution through a linear combination. We demonstrate that the present mechanism can produce very robust cooperative behavior in both games. Furthermore, we provide theoretical analysis based on mean-field approximation, and find that the analytical predictions are qualitatively consistent with the simulation results.
LIU Yong-Kui;LI Zhi;CHEN Xiao-Jie;WANG Long;. Evolutionary Self-Questioning Games with Local Contribution[J]. 中国物理快报, 2009, 26(8): 88902-088902.
LIU Yong-Kui, LI Zhi, CHEN Xiao-Jie, WANG Long,. Evolutionary Self-Questioning Games with Local Contribution. Chin. Phys. Lett., 2009, 26(8): 88902-088902.
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2009, Vol. 26 
