Full Text:   <255>

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CLC number: TP391.4

On-line Access: 2026-01-08

Received: 2025-02-14

Revision Accepted: 2025-07-31

Crosschecked: 2026-01-08

Cited: 0

Clicked: 899

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Shuai LIU

https://orcid.org/0000-0003-0523-022X

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Frontiers of Information Technology & Electronic Engineering  2025 Vol.26 No.11 P.2114-2127

http://doi.org/10.1631/FITEE.2500093


Privacy-preserving bipartite consensus with cooperative–competitive interactions via a node decomposition strategy


Author(s):  Licheng WANG, Yongling CHEN, Shuai LIU

Affiliation(s):  College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China; more

Corresponding email(s):   wanglicheng1217@163.com, chenyongling2024@163.com, liushuai871030@163.com

Key Words:  Privacy-preserving, Bipartite consensus, Cooperative–, competitive interactions, Multi-agent systems, Node decomposition


Licheng WANG, Yongling CHEN, Shuai LIU. Privacy-preserving bipartite consensus with cooperative–competitive interactions via a node decomposition strategy[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(11): 2114-2127.

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journal="Frontiers of Information Technology & Electronic Engineering",
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pages="2114-2127",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2500093"
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Abstract: 
This paper describes our investigation of the privacy protection problem of multi-agent systems under cooperative–;competitive networks. A node decomposition strategy is used to protect the privacy of the initial node values, in which a node vi is split into ni nodes. By designing inter-node weights, the initial value of each node is protected from honest-but-curious nodes and eavesdroppers without relying on external algorithms. The purpose is to design a privacy-preserving consensus algorithm such that the privacy performance is guaranteed by using the node decomposition strategy, while the bipartite consensus is achieved for the cooperative–;competitive multi-agent systems. Two numerical simulations are given to validate the effectiveness of the proposed privacy-preserving bipartite consensus algorithm.

基于节点分解隐私保护策略的合作-竞争二分一致性


王立成1,陈永玲2,刘帅2
1上海电力大学自动化工程学院,中国上海市,200090
2上海理工大学理学院,中国上海市,200093
摘要:本文研究了合作-竞争网络下多智能体系统的隐私保护问题。首先,采用节点分解策略保护节点初始值的隐私,该节点分解机制将每个节点vi分解为ni个节点。然后,通过设计节点间的权重,保护各节点初始值不被诚实但好奇的节点及窃听者获取,而无需依赖外部算法。目的在于设计一种隐私保护一致性算法,在利用节点分解策略保障隐私的同时,实现合作-竞争多智能体系统的二分一致性。给出两个数值仿真案例,以验证所提出的隐私保护二分一致性算法的有效性。

关键词:隐私保护;二分一致性;合作-竞争交互;多智能体系统;节点分解

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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