Distributed Algorithms for Searching Generalized Nash Equilibrium of Noncooperative Games

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 b...

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Vydáno v:IEEE transactions on cybernetics Ročník 49; číslo 6; s. 2362 - 2371
Hlavní autoři: Lu, Kaihong, Jing, Gangshan, Wang, Long
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Aggregates
Computer simulation
Consensus
Cost function
distributed algorithm
Distributed algorithms
Economic models
Game theory
Games
Linear equations
Mathematical model
Nash equilibrium
Nash equilibrium (NE)
noncooperative game
Nonlinear equations
Search algorithms
Search problems
ISSN:2168-2267, 2168-2275, 2168-2275
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Shrnutí: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.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2018.2828118