A damped forward-backward algorithm for stochastic generalized Nash equilibrium seeking
Optimization and Control
2020-02-17 v2 Computer Science and Game Theory
Systems and Control
Systems and Control
Abstract
We consider a stochastic generalized Nash equilibrium problem (GNEP) with expected-value cost functions. Inspired by Yi and Pavel (Automatica, 2019), we propose a distributed GNE seeking algorithm by exploiting the forward-backward operator splitting and a suitable preconditioning matrix. Specifically, we apply this method to the stochastic GNEP, where, at each iteration, the expected value of the pseudo-gradient is approximated via a number of random samples. Our main contribution is to show almost sure convergence of our proposed algorithm if the sample size grows large enough.
Cite
@article{arxiv.1910.11776,
title = {A damped forward-backward algorithm for stochastic generalized Nash equilibrium seeking},
author = {Barbara Franci and Sergio Grammatico},
journal= {arXiv preprint arXiv:1910.11776},
year = {2020}
}