Topology Estimation for Open Multi-Agent Systems
Provides a systematic solution for reconstructing interaction topologies in open multi-agent systems, a challenging problem for existing methods.
The paper tackles interaction topology identification in open multi-agent systems with dynamic node sets and fast switching. It proposes a projection-based dissimilarity measure for robust mode clustering, enabling accurate topology estimates despite short dwell times.
We address the problem of interaction topology identification in open multi-agent systems (OMAS) with dynamic node sets and fast switching interactions. In such systems, new agents join and interactions change rapidly, resulting in intervals with short dwell time and rendering conventional segment-wise estimation and clustering methods unreliable. To overcome this, we propose a projection-based dissimilarity measure derived from a consistency property of local least-squares operators, enabling robust mode clustering. Aggregating intervals within each cluster yields accurate topology estimates. The proposed framework offers a systematic solution for reconstructing the interaction topology of OMAS subject to fast switching. Finally, we illustrate our theoretical results via numerical simulations.