Distributed Generalized Nash Equilibrium Seeking in Aggregative Games on Time-Varying Networks

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Distributed Generalized Nash Equilibrium Seeking in Aggregative Games on Time-Varying Networks

Journal Article (2021)

Author(s)

Giuseppe Belgioioso (Eindhoven University of Technology)

Angelia Nedic (Arizona State University)

Sergio Grammatico (TU Delft - Mechanical Engineering)

Research Group

Team Bart De Schutter

Optimization method Network theory Distributed algorithms Multiagent systems

DOI related publication

https://doi.org/10.1109/TAC.2020.3005922 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:29c3f1db-0553-4138-82b9-d82aff1f42c9

More Info

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Publication Year

2021

Language

English

Research Group

Team Bart De Schutter

Issue number

5

Volume number

66

Pages (from-to)

2061-2075

Downloads counter

203

Abstract

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