Generalized Nash equilibrium seeking strategy for distributed nonsmooth multi-cluster game

Zeng, Xianlin; Chen, Jie; Liang, Shu; Ye, Hong

doi:10.1016/j.automatica.2019.01.025

Cited by 118 publications

(97 citation statements)

References 19 publications

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“…The algorithm has two interconnected dynamics. They predicted dynamics of gradient playback to search for the equilibrium with locally constrained sets of strategies [9] and distributed average tracking dynamics to evaluate aggregation [10]. In addition, paper [11] showed how to apply the dynamics of the distributed average tracking to the equilibrium by the weight of an oriented graph, which improves a learning algorithm.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Optimizing the strategy of activities using numerical methods for determining equilibrium

Sievidova¹,

Oliynik²,

Mandych³

et al. 2019

EEJET

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Optimizing the strategy of activities using numerical methods for determining equilibrium

Sievidova¹,

Oliynik²,

Mandych³

et al. 2019

EEJET

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“…Gossip‐based distributed algorithms were proposed in References 9,10 for networked games. The generalized Nash equilibrium seeking problems were investigated in References 11,12. Extremum seeking‐based algorithms were developed in References 13‐15 to address noncooperative games with nonquadratic payoffs.…”

Section: Introductionmentioning

confidence: 99%

Distributed adaptive Nash equilibrium seeking and disturbance rejection for noncooperative games of high‐order nonlinear systems with input saturation and input delay

Wang

2021

Intl J Robust & Nonlinear

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This article aims to investigate Nash equilibrium seeking problems for noncooperative games played by high-order nonlinear multiagent systems subject to input saturation, input delay, and external disturbances. Based on the gradient play technique, an adaptive Nash equilibrium seeking algorithm is designed in a distributed fashion via backstepping, where a fixed-time sliding mode observer is used to tackle the problem of "explosion of terms." In the proposed algorithm, an extended-state observer and an adaptive distributed observer are included for state/disturbance estimates and information sharing, respectively. Detailed convergence results are presented by leveraging Lyapunov stability theory. Finally, the effectiveness of the proposed approach is numerically verified through simulation results.

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“…The authors in [7]- [10] studied NE seeking for unconstrained N -coalition games. In [11], the inequality constraint is considered. However, the constraint is only related to one agent in each coalition.…”

Section: Introductionmentioning

confidence: 99%

“…As a comparison, [1], [7]- [10] studied NE seeking for unconstrained games while this work considers the GNE seeking for constrained games, which is more complicated. Compared with [11], the inequality constraints considered in this work are more general in the sense that multiple full constraints that may be related to all players' information are studied. While in [11], the inequality constraint is only related to one agent in each coalition;…”

Section: Introductionmentioning

confidence: 99%

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Distributed Nash Equilibrium Seeking for Generalized Convex Games with Shared Constraints

Sun

2018

J. Phys.: Conf. Ser.

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In this work, we investigate the distributed generalized Nash equilibrium (GNE) seeking problems for Ncoalition games with inequality constraints. First, we study the scenario where each agent in a coalition has full information of all the constraints. A finite-time average consensus-based approach is proposed by using full decision information. It is proven that the algorithm converges to a GNE (specifically, a variational equilibrium) of the game. Then, based on the finitetime consensus tracking, we propose a distributed algorithm by using partial decision information only, where only neighboring action information is needed for each agent. Furthermore, we investigate the scenario where only distributive constraint information is available for the agents. The terminology "distributive" here refers to the scenario where the constraint information acquisition and processing are conducted across multiple agents in a coalition, and each agent has access to only a subset of constraints, instead of the scenario where each agent has full information of all the constraints. In this case, the multiplier computation and the constraint information required for each individual are reduced. A full decision information algorithm and a partial decision information algorithm for this scenario are proposed, respectively. Numerical examples are given to verify the proposed algorithms.

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Generalized Nash equilibrium seeking strategy for distributed nonsmooth multi-cluster game

Cited by 118 publications

References 19 publications

Optimizing the strategy of activities using numerical methods for determining equilibrium

Optimizing the strategy of activities using numerical methods for determining equilibrium

Distributed adaptive Nash equilibrium seeking and disturbance rejection for noncooperative games of high‐order nonlinear systems with input saturation and input delay

Distributed Nash Equilibrium Seeking for Generalized Convex Games with Shared Constraints

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