Adaptive conformity promotes cooperation within structured populations

From an evolutionary perspective, the pursuit of individual payoff maximization is a widespread behavioral tendency. However, human decision-making is not solely driven by payoffs. Under conditions of uncertainty, risk aversion, and social pressure, individuals often abandon short-term optimal choices and instead conform to locally prevailing behaviors. Along this line, previous studies have investigated how conformity-driven influences the evolution of cooperation in social dilemmas by shaping network reciprocity. Nevertheless, most of these studies treat conformity as a static individual trait, which limits their ability to capture the fact that individuals in real societies flexibly adjust their conformity tendency in response to changing environments. Motivated by this perspective, we propose an adaptive conformity model and examine its impact on the evolution of cooperation in social dilemmas. In this model, individuals dynamically update their conformity tendency based on comparisons between local and global payoffs, with the updating process further modulated by a satisfaction threshold factor and memory length. Through systematic simulations across multiple types of social dilemmas and network topologies, we find that, compared with static conformity models, the adaptive conformity mechanism significantly expands the parameter region in which cooperation can emerge and persist. Specifically, the satisfaction threshold factor exerts a pronounced nonlinear effect on cooperation, whereas longer memory lengths generally suppress the emergence of cooperation. Importantly, even under more severe social dilemma conditions and highly heterogeneous network structures, the proposed model maintains a robust cooperation-promoting effect. These results suggest that adaptive conformity may provide a viable pathway toward mitigating social dilemmas.