2011/07/26 by Aram Galstyan, Galstyan, Aram, Ardeshir Kianercy +3
Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Computer Science and Game Theory (cs.GT) #Evolutionary Game Theory and Cooperation #FOS: Biological sciences #FOS: Computer and information sciences #Opinion Dynamics and Social Influence #Populations and Evolution (q-bio.PE) #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1107.5354
openalex publication_date 2011/07/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a simple model of network co-evolution in a game-dynamical system of interacting agents that play repeated games with their neighbors, and adapt their behaviors and network links based on the outcome of those games. The adaptation is achieved through a simple reinforcement learning scheme. We show that the collective evolution of such a system can be described by appropriately defined replicator dynamics equations. In particular, we suggest an appropriate factorization of the agents' strategies that results in a coupled system of equations characterizing the evolution of both strategies and network structure, and illustrate the framework on two simple examples.