Experience-driven learning and interactive rules under link weight adjustment promote cooperation in spatial prisoner's dilemma game

Drawing on social learning theory, which emphasizes the dual influence of direct and indirect experience on behavior, this study extends the Spatial Prisoner's Dilemma game framework through three key innovations. First, we develop a link weight adjustment mechanism that incorporates tolerance, a previously neglected factor. Second, we extend the interaction probability model by integrating both direct and indirect link weights. Third, we design a strategy update rule where behavioral adaptation depends on combined experience learning. Simulation results show that our approach significantly outperforms traditional models in promoting cooperation. In particular, we identify an inverse relationship between tolerance and cooperation levels, with reduced defection sensitivity effectively protecting cooperators from exploitation. Furthermore, indirect experiences prove more powerful than direct interactions in sustaining cooperation. Together, these mechanisms increase cooperators' payoffs and competitive advantage. Integrating both direct and indirect experiences into policy updates offers a more comprehensive approach to addressing complex social challenges, as it enables decision-makers to leverage both personal insights and collective wisdom for more effective solutions.