Evolution of cooperation on a dynamic network driven by reputation-dependent payoffs

Integrating reputation mechanisms with dynamic networks effectively facilitates collective cooperation in complex networks. However, existing studies only adjust network structures directly via reputation, ignoring the driving role of individual payoffs in network evolution. To address this gap, this paper proposes a reputation-payoff-network synergetic evolution framework and explores how reputation-dependent, payoff-driven dynamic networks promote cooperative behaviors. Results show that this synergetic evolution model significantly enhances collective cooperation, with its effectiveness depending on both the magnitude of the temptation to defect and the value of the reputation sensitivity factor. Specifically, when the temptation is small, the cooperation rate remains generally high, and the reputation sensitivity factor has no significant impact. In contrast, when the temptation is large, a high cooperation rate can be stably maintained only if the reputation sensitivity factor is small. This study confirms that regulating payoffs through reputation and subsequently allowing payoffs to drive the dynamic adjustment of network connections enables the establishment of an efficient cooperation-facilitating mechanism. Consequently, it provides new insights and theoretical support for guiding cooperative behaviors in complex networks.