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The work gives a review on the distributed Nash equilibrium seeking of noncooperative games in multi-agent networks, which emerges as one of the frontier research topics in the area of systems and control community. Firstly, we give the basic formulation and analysis of noncooperative games with continuous action spaces, and provide the motivation and basic setting for distributed Nash equilibrium seeking. Then we introduce both the gradient-based algorithms and best-response based algorithms for various type of games, including zero-sum games, aggregative games, potential games, monotone games, and multi-cluster games. In addition, we provide some applications of noncooperative games.


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A Survey on Noncooperative Games and Distributed Nash Equilibrium Seeking over Multi-Agent Networks

Show Author's information Peng Yi1,2Jinlong Lei1,2( )Xiuxian Li1,2Shu Liang1,2Min Meng1,2Jie Chen1,2
Department of Control Science and Engineering, Tongji University, Shanghai 201804, China
Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai 201210, China

Abstract

The work gives a review on the distributed Nash equilibrium seeking of noncooperative games in multi-agent networks, which emerges as one of the frontier research topics in the area of systems and control community. Firstly, we give the basic formulation and analysis of noncooperative games with continuous action spaces, and provide the motivation and basic setting for distributed Nash equilibrium seeking. Then we introduce both the gradient-based algorithms and best-response based algorithms for various type of games, including zero-sum games, aggregative games, potential games, monotone games, and multi-cluster games. In addition, we provide some applications of noncooperative games.

Keywords: distributed computation, Nash equilibrium, multi-agent systems, cyber-physical systems, noncooperative games, optimization and decision making

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Publication history

Received: 27 November 2021
Revised: 03 March 2022
Accepted: 17 June 2022
Published: 28 August 2022
Issue date: September 2022

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© The author(s) 2022

Acknowledgements

Acknowledgment

The authors would like to thank Xiaoyu Ma and Wenting Liu for their help in preparing the figures and tables. This work was supperted by Shanghai Sailing Program (Nos. 20YF1453000 and 20YF1452800), the National Science Foundation of China (Nos. 62003239, 62003240, 62003243, and 61903027), Shanghai Municipal Science and Technology Major Project (No. 2021SHZDZX0100), and Shanghai Municipal Commission of Science and Technology (No. 19511132101).

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