Distributed accelerated Nash equilibrium learning for two-subnetwork zero-sum game with bilinear coupling
This paper proposes a distributed accelerated first-order continuous-time algorithm for convergence to Nash equilibria in a class of two-subnetwork zero-sum games with bilinear couplings. First-order methods, which only use subgradients of functions, are frequently used in distributed/parallel algorithms for solving large-scale and big-data problems due to their simple structures. However, in the worst cases, first-order methods for two-subnetwork zero-sum games often have an asymptotic or convergence....