Paper Info
Title
Distributed Algorithms for Searching Generalized Nash Equilibrium of Noncooperative Games.
Abstract
In this paper, the distributed Nash equilibrium (NE) searching problem is investigated, where the feasible action sets are constrained by nonlinear inequalities and linear equations. Different from most of the existing investigations on distributed NE searching problems, we consider the case where both cost functions and feasible action sets depend on actions of all players, and each player can only have access to the information of its neighbors. To address this problem, a continuous-time distributed gradient-based projected algorithm is proposed, where a leader-following consensus algorithm is employed for each player to estimate actions of others. Under mild assumptions on cost functions and graphs, it is shown that players' actions asymptotically converge to a generalized NE. Simulation examples are presented to demonstrate the effectiveness of the theoretical results.
Year
DOI
Venue
2019
10.1109/TCYB.2018.2828118
IEEE transactions on cybernetics
Keywords
Field
DocType
Games,Cost function,Distributed algorithms,Search problems,Mathematical model,Aggregates,Nash equilibrium
Linear equation,Graph,Consensus algorithm,Mathematical optimization,Nonlinear system,Generalized nash equilibrium,Distributed algorithm,Nash equilibrium,Mathematics
Journal
Volume
Issue
ISSN
49
6
2168-2275
Citations 
PageRank 
References 
15
0.55
0
Authors
3
Name
Order
Citations
PageRank
Kaihong Lu1223.35
Gangshan Jing2707.05
Long Wang3434.58