The role of the preferred neighbor with the expected payoff on cooperation in spatial public goods game under optimal strategy selection mechanism

Abstract

Cooperation is considered to be one of the driving forces to advance human civilization. How to increase the level of cooperation within the community has always been a hot research topic. Combining complex network theory and evolutionary game theory provides a practical, theoretical framework for investigating this problem. However, previous researchers often focused on the network models reflecting the real physical structures and the game models representing the social dilemmas. Few people paid attention to the role of the individual specific behaviors in the evolutionary game process. In this paper, we propose two mechanisms, “the preferred neighbor with the expected payoff” and “the optimal strategy selection mechanism based on historical information,” to emulate individual actions in the two stages of selecting learning targets and choosing strategies, respectively. The preferred neighbor with the expected payoff mechanism can select learning objectives purposefully, avoiding the blindness caused by random selection in previous studies. The optimal strategy selection mechanism determines the best strategy by comprehensively considering the strategies and payoffs in a given time dimension to be used for the next game round robin. The simulation results demonstrate that either of the above two mechanisms can significantly promote the level of cooperation. If they join forces, the cooperation level of the system can be maximized to the greatest extent. Our work may provide some new approaches to increasing the overall cooperation levels from a brand-new perspective.