A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

Mathias Staudigl

doi:10.1109/CDC45484.2021.9682905

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

Mathias Staudigl

Research output: Contribution to conference › Poster › Academic

Abstract

We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

Original language	English
Pages	197-202
Number of pages	6
DOIs	https://doi.org/10.1109/CDC45484.2021.9682905
Publication status	Published - 2021
Event	60th Conference on Decision and Control - Online, Austin, United States Duration: 13 Dec 2021 → 17 Dec 2021 Conference number: 60 https://2021.ieeecdc.org/

Conference

Conference	60th Conference on Decision and Control
Abbreviated title	CDC2021
Country/Territory	United States
City	Austin
Period	13/12/21 → 17/12/21
Internet address	https://2021.ieeecdc.org/

Keywords

GAMES

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10.1109/CDC45484.2021.9682905

Cite this

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title = "A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking",

abstract = "We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.",

keywords = "GAMES",

author = "Mathias Staudigl",

note = "Funding Information: *This work was partially supported by NWO under research projects OMEGA (613.001.702) and P2P-TALES (647.003.003), and by the ERC under research project COSMOS (802348). Mathias Staudigl{\textquoteright}s research benefited from the support of the FMJH Program PGMO and from the support of EDF. Publisher Copyright: {\textcopyright} 2021 IEEE.; 60th Conference on Decision and Control, CDC2021 ; Conference date: 13-12-2021 Through 17-12-2021",

year = "2021",

doi = "10.1109/CDC45484.2021.9682905",

language = "English",

pages = "197--202",

url = "https://2021.ieeecdc.org/",

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T1 - A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

AU - Staudigl, Mathias

N1 - Conference code: 60

PY - 2021

Y1 - 2021

N2 - We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

AB - We propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. The proposed algorithm is derived from a forward-backward-forward scheme for solving structured monotone inclusion problems with Lipschitz continuous and monotone pseudogradient operator. To the best of our knowledge, this is the first distributed generalized Nash equilibrium seeking algorithm featuring acceleration techniques in stochastic Nash equilibrium problems without assuming cocoercivity. Numerical examples illustrate the effect of inertia and relaxation on the performance of our proposed algorithm.

KW - GAMES

U2 - 10.1109/CDC45484.2021.9682905

DO - 10.1109/CDC45484.2021.9682905

M3 - Poster

SP - 197

EP - 202

T2 - 60th Conference on Decision and Control

Y2 - 13 December 2021 through 17 December 2021

ER -

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking

Abstract

Conference

Keywords

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