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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2025 Vol.26 No.11 P.2114-2127
Privacy-preserving bipartite consensus with cooperative–competitive interactions via a node decomposition strategy
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.
Key words: Privacy-preserving; Bipartite consensus; Cooperative–competitive interactions; Multi-agent systems; Node decomposition
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。
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DOI:
10.1631/FITEE.2500093
CLC number:
TP391.4
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On-line Access:
2026-01-08
Received:
2025-02-14
Revision Accepted:
2025-07-31
Crosschecked:
2026-01-08