Stochastic generalized Nash equilibrium seeking under partial-decision information
Optimization and Control
2021-06-02 v2 Computer Science and Game Theory
Systems and Control
Systems and Control
Abstract
We consider for the first time a stochastic generalized Nash equilibrium problem, i.e., with expected-value cost functions and joint feasibility constraints, under partial-decision information, meaning that the agents communicate only with some trusted neighbours. We propose several distributed algorithms for network games and aggregative games that we show being special instances of a preconditioned forward-backward splitting method. We prove that the algorithms converge to a generalized Nash equilibrium when the forward operator is restricted cocoercive by using the stochastic approximation scheme with variance reduction to estimate the expected value of the pseudogradient.
Cite
@article{arxiv.2011.05357,
title = {Stochastic generalized Nash equilibrium seeking under partial-decision information},
author = {Barbara Franci and Sergio Grammatico},
journal= {arXiv preprint arXiv:2011.05357},
year = {2021}
}