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

Conference paper (2019)

Authors

Giuseppe Belgioioso Eindhoven University of Technology
Angelia Nedic Arizona State University
S. Grammatico Team Sergio Grammatico - Mechanical, Maritime and Materials Engineering ,
Research Group
Team Sergio Grammatico (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2019

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Sergio Grammatico

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.

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