Adaptive approaches for fully distributed Nash equilibrium seeking in networked games

This paper considers the design of fully distributed Nash equilibrium seeking strategies for networked games. To develop strategies, two adaptive control laws, including a node-based law and an edge-based law, are proposed. In strategy, each player adjusts their own weight on procurable consensus error dynamically. Moreover, in algorithm, strategy is designed by adding adaptively adjusted scaling parameter to weights edges communication graph . With proposed methods free any centralized gains, i.e., players can update actions without knowing information. By utilizing LaSalle’s invariance principle, it shown that globally asymptotically stable under both strategies. addition, we further show method be easily adapted accommodate time-varying conditions, which network switching among set undirected connected graphs. last, numerical examples given illustrate effectiveness methods.