Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159486
Title: Distributed Nash equilibrium seeking with limited cost function knowledge via a consensus-based gradient-free method
Authors: Pang, Yipeng
Hu, Guoqiang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Pang, Y. & Hu, G. (2021). Distributed Nash equilibrium seeking with limited cost function knowledge via a consensus-based gradient-free method. IEEE Transactions On Automatic Control, 66(4), 1832-1839. https://dx.doi.org/10.1109/TAC.2020.2995666
Project: RG180/17(2017-T1-002- 158)
NRF2013EWT-EIRP004-051
Journal: IEEE Transactions on Automatic Control
Abstract: This article considers a distributed Nash equilibrium seeking problem, where the players only have partial access to other players' actions, such as their neighbors' actions. Thus, the players are supposed to communicate with each other to estimate other players' actions. To solve the problem, a leader-following consensus gradient-free distributed Nash equilibrium seeking algorithm is proposed. This algorithm utilizes only the measurements of the player' local cost function without the knowledge of its explicit expression or the requirement on its smoothness. Hence, the algorithm is gradient-free during the entire updating process. Moreover, the analysis on the convergence of the Nash equilibrium is studied for the algorithm with both diminishing and constant step-sizes, respectively. Specifically, in the case of diminishing step-size, it is shown that the players' actions converge to the Nash equilibrium almost surely, while in the case of fixed step-size, the convergence to the neighborhood of the Nash equilibrium is achieved. The performance of the proposed algorithm is verified through numerical simulations.
URI: https://hdl.handle.net/10356/159486
ISSN: 0018-9286
DOI: 10.1109/TAC.2020.2995666
Schools: School of Electrical and Electronic Engineering 
Rights: © 2020 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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