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Volume 34, Issue 6
June 2024
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Research Article| June 25 2024
Xin Jin
;
Xin Jin
(Formal analysis, Investigation, Writing – original draft, Writing – review & editing)
1
School of Mathematical Sciences, University of Electronic Science and Technology of China
, Chengdu 611731,
China
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Kaihong Lu;
Kaihong Lu
(Formal analysis, Writing – original draft, Writing – review & editing)
2
College of Electrical Engineering and Automation, Shandong University of Science and Technology
, Qingdao 266590,
China
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Zhengxin Wang;
Zhengxin Wang
(Formal analysis, Writing – original draft, Writing – review & editing)
3
School of Science, Nanjing University of Posts and Telecommunications
, Nanjing 210023,
China
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Xiaojie Chen
Xiaojie Chen a)
(Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing)
1
School of Mathematical Sciences, University of Electronic Science and Technology of China
, Chengdu 611731,
China
a)Author to whom correspondence should be addressed: xiaojiechen@uestc.edu.cn
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Author & Article Information
a)Author to whom correspondence should be addressed: xiaojiechen@uestc.edu.cn
Chaos 34, 063141 (2024)
Article history
Received:
April 22 2024
Accepted:
May 31 2024
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Citation
Xin Jin, Kaihong Lu, Zhengxin Wang, Xiaojie Chen; Distributed Nash equilibrium seeking in noncooperative game with partial decision information of neighbors. Chaos 1 June 2024; 34 (6): 063141. https://doi.org/10.1063/5.0215214
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In the real world, individuals may conceal some of their real decision information to their neighbors due to competition. It is a challenge to explore the distributed Nash equilibrium when individuals play the noncooperative game with partial decision information in complex networks. In this paper, we investigate the distributed Nash equilibrium seeking problem with partial decision information of neighbors. Specifically, we construct a two-layer network model, where players in the first layer engage in game interactions and players in the second layer exchange estimations of real actions with each other. We also consider the case where the actions of some players remain unchanged due to the cost of updating or personal reluctance. By means of the Lyapunov function method and LaSalle’s invariance principle, we obtain the sufficient conditions in which the consensus of individual actions and estimations can be achieved and the population actions can converge to the Nash equilibrium point. Furthermore, we investigate the case with switched topologies and derive the sufficient conditions for the convergence of individual actions to Nash equilibrium by the average dwell time method. Finally, we give numerical examples for cases of fixed and switched topologies to verify our theoretical results.
Topics
Lyapunov stability, Friction, Telecommunication networks, Algorithms and data structure, Cognitive science, Optimization algorithms, Game theory, Network theory, Operator theory, Optimization problems
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© 2024 Author(s). Published under an exclusive license by AIP Publishing.
2024
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