A damped forward-backward algorithm for stochastic generalized Nash equilibrium seeking

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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.

Original languageEnglish
Title of host publicationProceedings of the European Control Conference 2020, ECC 2020
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages1117-1122
ISBN (Electronic)978-3-907144-01-5
ISBN (Print)978-3-907144-02-2
Publication statusPublished - 2020
Event18th European Control Conference, ECC 2020 - Saint Petersburg, Russian Federation
Duration: 12 May 202015 May 2020

Conference

Conference18th European Control Conference, ECC 2020
CountryRussian Federation
CitySaint Petersburg
Period12/05/2015/05/20

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