Nash Equilibrium Computation in Subnetwork Zero-Sum Games With Switching Communications

Authors:
Top Cited Papers
Publisher website
Google Scholar
Abstract
In this paper, we investigate a distributed Nash equilibrium computation problem for a time-varying multi-agent network consisting of two subnetworks, where the two subnetworks share the same objective function. We first propose a subgradient-based distributed algorithm with heterogeneous stepsizes to compute a Nash equilibrium of a zero-sum game. We then prove that the proposed algorithm can achieve a Nash equilibrium under uniformly jointly strongly connected (UJSC) weight-balanced digraphs with homogenous stepsizes. Moreover, we demonstrate that for weighted-unbalanced graphs a Nash equilibrium may not be achieved with homogenous stepsizes unless certain conditions on the objective function hold. We show that there always exist heterogeneous stepsizes for the proposed algorithm to guarantee that a Nash equilibrium can be achieved for UJSC digraphs. Finally, in two standard weight-unbalanced cases, we verify the convergence to a Nash equilibrium by adaptively updating the stepsizes along with the arc weights in the proposed algorithm.
Funding Information
  • NNSF of China (71401163, 61333001)
  • Hong Kong Scholars Program (XJ2015049)
  • Beijing Natural Science Foundation (4152057)
  • National Research Foundation of Singapore (NRF-CRP8-2011-03)
  • Knut and Alice Wallenberg Foundation
  • Swedish Research Council

This publication has 33 references indexed in Scilit: