A resilient distributed optimization algorithm based on consensus of multi-agent system against two attack scenarios

Chentao Xu; Qingshan Liu

doi:10.1016/j.jfranklin.2022.08.031

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A resilient distributed optimization algorithm based on consensus of multi-agent system against two attack scenarios

Chentao Xu Qingshan Liu

Year: 2022 Journal: Journal of the Franklin Institute Vol: 360 (12)Pages: 9096-9114 Publisher: Elsevier BV

DOI: 10.1016/j.jfranklin.2022.08.031

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Keywords:

Computer science Convergence (economics) Enhanced Data Rates for GSM Evolution Algorithm Node (physics) Attack model Range (aeronautics) Multi-agent system Graph Mathematical optimization Mathematics Theoretical computer science Computer security Artificial intelligence Engineering

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Distributed Control Multi-Agent Systems

Physical Sciences → Computer Science → Computer Networks and Communications

Neural Networks Stability and Synchronization

Physical Sciences → Computer Science → Computer Networks and Communications

Mathematical and Theoretical Epidemiology and Ecology Models

Health Sciences → Medicine → Public Health, Environmental and Occupational Health

A resilient distributed optimization algorithm based on consensus of multi-agent system against two attack scenarios

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