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Consensus and Cooperation in Networked Multi-Agent Systems

2007/01/01 by Reza Olfati-Saber, Reza Olfati‐Saber, J. Alex Fax +2 · 10,396 citations
Computer Science · Mathematics · Physics and Astronomy · #Algebraic graph theory #Algorithm #Artificial intelligence #Complex network #Computer network #Computer science #Consensus #Consensus algorithm #Distributed Control Multi-Agent Systems #Distributed computing #Flocking (texture) #Gossip #Graph theory #Machine learning #Markov chain #Mathematics #Multi-agent system #Network topology #Neural Networks Stability and Synchronization #Opinion Dynamics and Social Influence #Rendezvous #Robustness (evolution) #Theoretical computer science #Topology (electrical circuits)

paper · doi:10.1109/jproc.2006.887293

published in Proceedings of the IEEE 95(1), 215-233 (Institute of Electrical and Electronics Engineers)

openalex publication_date 2007/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, distributed sensor fusion in sensor networks, and belief propagation. We establish direct connections between spectral and structural properties of complex networks and the speed of information diffusion of consensus algorithms. A brief introduction is provided on networked systems with nonlocal information flow that are considerably faster than distributed systems with lattice-type nearest neighbor interactions. Simulation results are presented that demonstrate the role of small-world effects on the speed of consensus algorithms and cooperative control of multivehicle formations.

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