Paper Info
Title
Nonsmooth Continuous-Time Distributed Algorithms for Seeking Generalized Nash Equilibria of Noncooperative Games via Digraphs
Abstract
In this article, the problem of distributed generalized Nash equilibrium (GNE) seeking in noncooperative games is investigated via multiagent networks, where each player aims to minimize his or her own cost function with a nonsmooth term. Each player’s cost function and feasible action set in the noncooperative game are both determined by actions of others who may not be neighbors, as well as his/her own action. Particularly, feasible action sets are constrained by private convex inequalities and shared linear equations. Each player can only have access to his or her own cost function, private constraint, and a local block of shared constraints, and can only communicate with his or her neighbours via a digraph. To address this problem, a novel continuous-time distributed primal–dual algorithm involving Clarke’s generalized gradient is proposed based on consensus algorithms and the primal–dual algorithm. Under mild assumptions on cost functions and graph, we prove that players’ actions asymptotically converge to a GNE. Finally, a simulation is presented to demonstrate the effectiveness of our theoretical results.
Year
DOI
Venue
2022
10.1109/TCYB.2021.3049463
IEEE Transactions on Cybernetics
Keywords
DocType
Volume
Algorithms,Computer Simulation,Female,Humans,Male
Journal
52
Issue
ISSN
Citations 
7
2168-2267
0
PageRank 
References 
Authors
0.34
33
2
Name
Order
Citations
PageRank
Kaihong Lu1223.35
Qixin Zhu215618.69