Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking

Barbara Franci; Mathias Staudigl; Sergio Grammatico

doi:10.23919/ECC51009.2020.9143676

Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking

Barbara Franci^*, Mathias Staudigl, Sergio Grammatico

^*Corresponding author for this work

Advanced Computing Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

We present two distributed algorithms for the computation of a generalized Nash equilibrium in monotone games. The first algorithm follows from a forward-backward-forward operator splitting, while the second, which requires the pseudo-gradient mapping of the game to be cocoercive, follows from the forward-backward-half-forward operator splitting. Finally, we compare them with the distributed, preconditioned, forward-backward algorithm via numerical experiments.

Original language	English
Title of host publication	European Control Conference 2020, ECC 2020
Publisher	IEEE Xplore
Pages	1274-1279
Number of pages	6
ISBN (Electronic)	978-3-90714-402-2
DOIs	https://doi.org/10.23919/ECC51009.2020.9143676
Publication status	Published - 2020
Event	2020 European Control Conference - Russia, Saint Petersburg, Russian Federation Duration: 12 May 2020 → 15 May 2020 https://ieeexplore.ieee.org/document/9143676/authors#authors

Conference

Conference	2020 European Control Conference
Abbreviated title	ECC 2020
Country/Territory	Russian Federation
City	Saint Petersburg
Period	12/05/20 → 15/05/20
Internet address	https://ieeexplore.ieee.org/document/9143676/authors#authors

Access to Document

10.23919/ECC51009.2020.9143676

Cite this

@inproceedings{092fde1899904e3389de4b790231748c,

title = "Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking",

abstract = "We present two distributed algorithms for the computation of a generalized Nash equilibrium in monotone games. The first algorithm follows from a forward-backward-forward operator splitting, while the second, which requires the pseudo-gradient mapping of the game to be cocoercive, follows from the forward-backward-half-forward operator splitting. Finally, we compare them with the distributed, preconditioned, forward-backward algorithm via numerical experiments.",

author = "Barbara Franci and Mathias Staudigl and Sergio Grammatico",

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). M. Staudigl acknowledges support from the COST Action CA16228 {"}European Network form Game Theory{"}. 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). M. Staudigl acknowledges support from the COST Action CA16228 ”European Network form Game Theory”. Publisher Copyright: {\textcopyright} 2020 EUCA.; 2020 European Control Conference, ECC 2020 ; Conference date: 12-05-2020 Through 15-05-2020",

year = "2020",

doi = "10.23919/ECC51009.2020.9143676",

language = "English",

pages = "1274--1279",

booktitle = "European Control Conference 2020, ECC 2020",

publisher = "IEEE Xplore",

url = "https://ieeexplore.ieee.org/document/9143676/authors#authors",

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TY - GEN

T1 - Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking

AU - Franci, Barbara

AU - Staudigl, Mathias

AU - Grammatico, Sergio

N1 - 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). M. Staudigl acknowledges support from the COST Action CA16228 "European Network form Game Theory". 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). M. Staudigl acknowledges support from the COST Action CA16228 ”European Network form Game Theory”. Publisher Copyright: © 2020 EUCA.

PY - 2020

Y1 - 2020

N2 - We present two distributed algorithms for the computation of a generalized Nash equilibrium in monotone games. The first algorithm follows from a forward-backward-forward operator splitting, while the second, which requires the pseudo-gradient mapping of the game to be cocoercive, follows from the forward-backward-half-forward operator splitting. Finally, we compare them with the distributed, preconditioned, forward-backward algorithm via numerical experiments.

AB - We present two distributed algorithms for the computation of a generalized Nash equilibrium in monotone games. The first algorithm follows from a forward-backward-forward operator splitting, while the second, which requires the pseudo-gradient mapping of the game to be cocoercive, follows from the forward-backward-half-forward operator splitting. Finally, we compare them with the distributed, preconditioned, forward-backward algorithm via numerical experiments.

U2 - 10.23919/ECC51009.2020.9143676

DO - 10.23919/ECC51009.2020.9143676

M3 - Conference article in proceeding

SP - 1274

EP - 1279

BT - European Control Conference 2020, ECC 2020

PB - IEEE Xplore

T2 - 2020 European Control Conference

Y2 - 12 May 2020 through 15 May 2020

ER -