Abstract
We study a simple but compelling model of network of agents interacting via time-dependent communication links. The model finds application in a variety of fields including synchronization, swarming and distributed decision making. In the model, each agent updates his current state based upon the current information received from neighboring agents. Necessary and/or sufficient conditions for the convergence of the individual agents' states to a common value are presented, thereby extending recent results reported in the literature. The stability analysis is based upon a blend of graph-theoretic and system-theoretic tools with the notion of convexity playing a central role. The analysis is integrated within a formal framework of set-valued Lyapunov theory, which may be of independent interest. Among others, it is observed that more communication does not necessarily lead to faster convergence and may eventually even lead to a loss of convergence, even for the simple models discussed in the present paper.
Keywords
Computer scienceConvergence (economics)ConvexityLyapunov functionMulti-agent systemSimple (philosophy)Synchronization (alternating current)Graph theoryGraphStability (learning theory)Mathematical optimizationDistributed computingDirected graphTheoretical computer scienceMathematicsArtificial intelligenceNonlinear systemAlgorithmMachine learningTelecommunications
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Publication Info
- Year
- 2005
- Type
- article
- Volume
- 50
- Issue
- 2
- Pages
- 169-182
- Citations
- 2707
- Access
- Closed
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Cite This
Luc Moreau
(2005).
Stability of multiagent systems with time-dependent communication links.
IEEE Transactions on Automatic Control
, 50
(2)
, 169-182.
https://doi.org/10.1109/tac.2004.841888
Identifiers
- DOI
- 10.1109/tac.2004.841888