Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking

Giuseppe Belgioioso; Angelia Nedic; Sergio Grammatico

doi:10.1109/CDC40024.2019.9029883

Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking

Giuseppe Belgioioso, Angelia Nedic, Sergio Grammatico

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

3 Citations (Scopus)

Abstract

We design a distributed algorithm for generalized Nash equilibrium seeking in aggregative games with linear coupling constraints under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by including dynamic tracking together with a standard projected pseudo-gradient algorithm in a fully-distributed fashion. The convergence analysis of the algorithm relies on the framework of monotone operator splitting and Krasnosel'skii-Mann fixed-point iteration with errors.

Original language	English
Title of host publication	Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019
Publisher	IEEE
Pages	5948-5954
ISBN (Electronic)	978-1-7281-1398-2
DOIs	https://doi.org/10.1109/CDC40024.2019.9029883
Publication status	Published - 2019
Event	58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France Duration: 11 Dec 2019 → 13 Dec 2019

Conference

Conference	58th IEEE Conference on Decision and Control, CDC 2019
Country/Territory	France
City	Nice
Period	11/12/19 → 13/12/19

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10.1109/CDC40024.2019.9029883

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title = "Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking",

abstract = "We design a distributed algorithm for generalized Nash equilibrium seeking in aggregative games with linear coupling constraints under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by including dynamic tracking together with a standard projected pseudo-gradient algorithm in a fully-distributed fashion. The convergence analysis of the algorithm relies on the framework of monotone operator splitting and Krasnosel'skii-Mann fixed-point iteration with errors.",

author = "Giuseppe Belgioioso and Angelia Nedic and Sergio Grammatico",

year = "2019",

doi = "10.1109/CDC40024.2019.9029883",

language = "English",

pages = "5948--5954",

booktitle = "Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019",

publisher = "IEEE",

address = "United States",

note = "58th IEEE Conference on Decision and Control, CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

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Belgioioso, G, Nedic, A & Grammatico, S 2019, Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking. in Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019. IEEE, pp. 5948-5954, 58th IEEE Conference on Decision and Control, CDC 2019, Nice, France, 11/12/19. https://doi.org/10.1109/CDC40024.2019.9029883

Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking. / Belgioioso, Giuseppe; Nedic, Angelia; Grammatico, Sergio.
Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019. IEEE, 2019. p. 5948-5954.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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N2 - We design a distributed algorithm for generalized Nash equilibrium seeking in aggregative games with linear coupling constraints under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by including dynamic tracking together with a standard projected pseudo-gradient algorithm in a fully-distributed fashion. The convergence analysis of the algorithm relies on the framework of monotone operator splitting and Krasnosel'skii-Mann fixed-point iteration with errors.

AB - We design a distributed algorithm for generalized Nash equilibrium seeking in aggregative games with linear coupling constraints under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by including dynamic tracking together with a standard projected pseudo-gradient algorithm in a fully-distributed fashion. The convergence analysis of the algorithm relies on the framework of monotone operator splitting and Krasnosel'skii-Mann fixed-point iteration with errors.

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DO - 10.1109/CDC40024.2019.9029883

M3 - Conference contribution

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BT - Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019

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T2 - 58th IEEE Conference on Decision and Control, CDC 2019

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ER -

Distributed generalized Nash equilibrium seeking in aggregative games under partial-decision information via dynamic tracking

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