SYSYOCFeb 9, 2019

Symmetry-Induced Clustering in Multi-Agent Systems using Network Optimization and Passivity

arXiv:1902.034103 citationsh-index: 29
AI Analysis

Provides a theoretical framework for clustering in multi-agent systems, relevant for control and coordination problems.

This work shows that diffusively-coupled multi-agent systems with maximally equilibrium independent passive agents and controllers converge to a clustered steady-state, where clusters correspond to symmetries defined by the exchangeability graph. It also addresses the cluster synthesis problem for homogeneous networks.

This work studies the effects of a weak notion of symmetry on diffusively-coupled multi-agent systems. We focus on networks comprised of agents and controllers which are maximally equilibrium independent passive, and show that these converge to a clustered steady-state, with clusters corresponding to certain symmetries of the system. Namely, clusters are computed using the notion of the exchangeability graph. We then discuss homogeneous networks and the cluster synthesis problem, namely finding a graph and homogeneous controllers forcing the agents to cluster at prescribed values.

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