Formation of Robust Multi-Agent Networks Through Self-Organizing Random Regular Graphs

A. Yasin Yazicioglu; Magnus Egerstedt; Jeff S. Shamma

doi:10.1109/tnse.2015.2503983

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arXiv · 1503.08131

Formation of Robust Multi-Agent Networks Through Self-Organizing Random Regular Graphs

A. Yasin Yazicioglu·Magnus Egerstedt·Jeff S. Shamma

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Abstract

Multi-agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m in [k, k + 2]. Accordingly, the agents improve the robustness of the network with a minimal change in the overall sparsity by optimizing the graph connectivity through the proposed local operations.

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A. Yasin Yazicioglu, Magnus Egerstedt, Jeff S. Shamma. 2015-03-27. Formation of Robust Multi-Agent Networks Through Self-Organizing Random Regular Graphs. https://doi.org/10.1109/tnse.2015.2503983

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