A Communication-Efficient and Differentially-Private Distributed Generalized Nash Equilibrium Seeking Algorithm for Aggregative Games

Fuente: arXiv
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Main Authors: Zhao, Wenqing, Xie, Antai, Wu, Yuchi, Yi, Xinlei, Ren, Xiaoqiang
Format: Preprint
Published: 2025
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author Zhao, Wenqing
Xie, Antai
Wu, Yuchi
Yi, Xinlei
Ren, Xiaoqiang
author_facet Zhao, Wenqing
Xie, Antai
Wu, Yuchi
Yi, Xinlei
Ren, Xiaoqiang
contents This paper studies the distributed generalized Nash equilibrium seeking problem for aggregative games with coupling constraints, where each player optimizes its strategy depending on its local cost function and the estimated strategy aggregation. The information transmission in distributed networks may go beyond bandwidth capacity and eventuate communication bottlenecks. Therefore, we propose a novel communication-efficient distributed generalized Nash equilibrium seeking algorithm, in which the communication efficiency is improved by event-triggered communication and information compression methods. The proposed algorithm saves the transmitted rounds and bits of communication simultaneously. Specifically, by developing precise step size conditions, the proposed algorithm ensures provable convergence, and is proven to achieve $(0,δ)$-differential privacy with a stochastic quantization scheme. In the end, simulation results verify the effectiveness of the proposed algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2503_08494
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Communication-Efficient and Differentially-Private Distributed Generalized Nash Equilibrium Seeking Algorithm for Aggregative Games
Zhao, Wenqing
Xie, Antai
Wu, Yuchi
Yi, Xinlei
Ren, Xiaoqiang
Optimization and Control
This paper studies the distributed generalized Nash equilibrium seeking problem for aggregative games with coupling constraints, where each player optimizes its strategy depending on its local cost function and the estimated strategy aggregation. The information transmission in distributed networks may go beyond bandwidth capacity and eventuate communication bottlenecks. Therefore, we propose a novel communication-efficient distributed generalized Nash equilibrium seeking algorithm, in which the communication efficiency is improved by event-triggered communication and information compression methods. The proposed algorithm saves the transmitted rounds and bits of communication simultaneously. Specifically, by developing precise step size conditions, the proposed algorithm ensures provable convergence, and is proven to achieve $(0,δ)$-differential privacy with a stochastic quantization scheme. In the end, simulation results verify the effectiveness of the proposed algorithm.
title A Communication-Efficient and Differentially-Private Distributed Generalized Nash Equilibrium Seeking Algorithm for Aggregative Games
topic Optimization and Control
url https://arxiv.org/abs/2503.08494