Distributed Nash equilibrium learning: A second‐order proximal algorithm
Wei Pan, Yu Ying Lu, Zehua Jia, Weidong Zhang · International Journal of Robust and Nonlinear Control · 2021
Abstract This article addresses the distributed Nash equilibrium (NE) seeking problem for multiagent networked games with partial decision information. We employ a quadratically approximated alternating direction method of multipliers together with an augmented consensus procedure to compute the NE of games with twice differentiable cost functions. The resulting second‐order proximal algorithm enjoys relatively fast convergence rate and less burden on step size selection compared with the existing works. Numerical simulations are consistent with our theoretical analysis.