Resilient Distributed Optimization

被引：1
|
作者：
Zhu, Jingxuan [1 ]
Lin, Yixuan [1 ]
Velasquez, Alvaro [2 ]
Liu, Ji [3 ]
机构：
[1] SUNY Stony Brook, Dept Appl Math & Stat, Stony Brook, NY 11794 USA
[2] Univ Colorado, Dept Comp Sci, Boulder, CO USA
[3] SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY USA
来源：
2023 AMERICAN CONTROL CONFERENCE, ACC | 2023年
基金：
美国国家科学基金会;
关键词：
D O I：
10.23919/ACC55779.2023.10156564
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper considers a distributed optimization problem in the presence of Byzantine agents capable of introducing untrustworthy information into the communication network. A resilient distributed subgradient algorithm is proposed based on graph redundancy and objective redundancy. It is shown that the algorithm causes all non-Byzantine agents' states to asymptotically converge to the same optimal point under appropriate assumptions. A partial convergence rate result is also provided.
引用
收藏
页码：1307 / 1312
页数：6
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