Analysis and Control of Networked Game Dynamics via A Microscopic Deterministic Approach

Networked games prevail in a wide range of evolutionary collective phenomena on social, biological, and engineering networks. An important and challenging problem is how to understand and then further intervene in the evolutionary networked game dynamics. This technical note aims at developing a microscopic deterministic formulation for analyzing and controlling the evolutionary game dynamics on complex networks. By utilizing the typical characteristics of multi-agent systems, the proposed approach establishes a systematic framework with micro-macro-intervention mechanism to analyze and control the networked game dynamics. Based on the proposed method, this technical note further explores several key issues, including consensus of strategies, cooperation among individuals and control of the network game dynamics. These results indicate us that the feedback from neighborhoods to each individual can alter the tendency of defection for adaptive dynamics. While for imitation dynamics on networks, it is much more effective to boost cooperation by awarding cooperators with high degree. Moreover, the effectiveness of different cooperation mechanisms has been clarified. The developed microscopic deterministic approach sheds some lights on the understanding and intervening in the collective decision-making behaviors in social and engineering networks.