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

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

Conference Paper (2019)

Author(s)

Giuseppe Belgioioso (Eindhoven University of Technology)

Angelia Nedic (Arizona State University)

Sergio Grammatico (TU Delft - Mechanical Engineering, TU Delft - Mechanical Engineering)

Research Group

Team Sergio Grammatico

DOI related publication

https://doi.org/10.1109/CDC40024.2019.9029883 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:a2630e59-b1ca-4c81-87d7-a333b25090c6

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Publication Year

2019

Language

English

Research Group

Team Sergio Grammatico

Pages (from-to)

5948-5954

ISBN (electronic)

978-1-7281-1398-2

Event

58th IEEE Conference on Decision and Control, CDC 2019 (2019-12-11 - 2019-12-13), Nice, France

Downloads counter

186

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.