Cooperation dynamics in multilayer networks under recommendation and vigilance mechanisms

This paper presents a multilayer network game model to explore the dynamics of cooperation in structured populations. The model integrates a static lower-layer relationship network, where nodes represent agents and edges reflect the strength of their social ties, with a dynamic upper-layer game network, where interactions are determined probabilistically based on relationship strengths. The model employs a Prisoner’s Dilemma framework to capture strategic decision-making and also introduces two mechanisms — recommendation and vigilance — to simulate trust propagation and reputation effects. Through extensive simulations, we demonstrate that cooperation levels are significantly influenced by network structure, with scale-free networks exhibiting greater resilience to defection compared to regular or small-world networks. Additionally, we analyze the impact of some key parameters, including the temptation to defect, interaction thresholds, and fitness weights, on cooperation outcomes. The results underscore the critical role of network topology and social mechanisms in shaping cooperative behavior, providing valuable insights into the interplay between network structure and strategic interactions.