In our work, we study the coevolution of cooperative behavior and individual perception through the lens of evolutionary game theory, considering the adoption of a disease containment measure as a cooperative act. We introduce this general game-theoretical framework as the “norm compliance dilemma,” where the evolution of agents' behaviors depends on their distinct, time-evolving perceptions. Starting from a simplified model of a well-mixed infinite population having homogeneous perceptions, we study and analytically solve a system of ordinary differential equations to predict the game equilibria. Subsequently, we compare the theoretical results with those obtained in finite populations having heterogeneous individual perceptions and organized in a network structure. We show that disease prevalence promotes cooperation, finding that this result is confirmed regardless of the spatial arrangement of individuals or the heterogeneity of their perception. However, networked structures can hinder and slow the evolution of cooperation with respect to well-mixed populations. Our findings highlight the crucial role of individual perception in shaping cooperative behavior and suggest that while disease prevalence increases norm compliance, the underlying population structure significantly influences the dynamics of cooperation.

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• Collective behavior in networks
• Evolutionary games
• Monte Carlo methods