Nash equilibrium seeking under partial-decision information: monotonicity, smoothness and proximal-point algorithms

Conference paper (2022)

Authors

M. Bianchi Team Sergio Grammatico - Mechanical, Maritime and Materials Engineering
S. Grammatico Team Sergio Grammatico - Mechanical, Maritime and Materials Engineering ,
Research Group
Team Sergio Grammatico (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 M. Bianchi, S. Grammatico
DOI: https://doi.org/10.1109/CDC51059.2022.9993145
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Published Date

2022

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 consider Nash equilibrium problems in a partial-decision information scenario, where each agent can only exchange information with some neighbors, while its cost function possibly depends on the strategies of all agents. We characterize the relation between several monotonicity and smoothness assumptions postulated in the literature. Furthermore, we prove convergence of a preconditioned proximal-point algorithm, under a restricted monotonicity property that allows for a non-Lipschitz, non-continuous game mapping.

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