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 str...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.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 70671079, 60674050, 60736022 and 60528007, the National Basic Research Program of China under Grant No 2002CB312200, the National High-Tech Research and Development Program of China under Grant No 2006AA04Z258, the 11-5 Project under Grant No A2120061303, and China Scholarship Council under Grant No 2008100772.
文摘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.
