Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, China.
School of Artificial Intelligence, Tiangong University, Tianjin 300387, China.
Chaos. 2023 Oct 1;33(10). doi: 10.1063/5.0157761.
Network typology largely affects the evolutionary dynamics of collective behaviors in many real-world complex systems. As a conventional transmission model, the sender-receiver game paves the way to explore the evolution of honest signals between senders and receivers. In practice, the utilities of an agent often depend not only on pairwise interactions, but also on the group influence of players around them, and thus there is an urgent need for deeper theoretical modeling and investigations on individuals' non-pairwise interactions. Considering the underlying evolutionary game dynamics and multiple community network structures, we explore the evolution of honest behaviors by extending the sender-receiver game to multiple communities. With the new dynamical model of the multi-community system, we perform a stability analysis of the system equilibrium state. Our results reveal the condition to promote the evolution of honest behaviors and provide an effective method for enhancing collaboration behaviors in distributed complex systems. Current results help us to deeply understand how collective decision-making behaviors evolve, influenced by the spread of true information and misinformation in large dynamic systems.
网络拓扑结构在很大程度上影响着许多现实复杂系统中集体行为的演化动态。作为一种传统的传播模型，发送者-接收者博弈为探索发送者和接收者之间诚实信号的演化铺平了道路。在实际中，一个主体的效用不仅取决于两两相互作用，还取决于其周围参与者的群体影响，因此，迫切需要对个体的非两两相互作用进行更深入的理论建模和研究。考虑到潜在的演化博弈动态和多个社区网络结构，我们通过将发送者-接收者博弈扩展到多个社区来探索诚实行为的演化。通过多社区系统的新动力学模型，我们对系统平衡态的稳定性进行了分析。研究结果揭示了促进诚实行为演化的条件，并为增强分布式复杂系统中的协作行为提供了一种有效方法。目前的研究结果有助于我们深入理解在大型动态系统中真实信息和错误信息传播如何影响集体决策行为的演化。
