Multi-Agent Control: A Graph-Theoretic Perspective

Abstract

Progress in development of multi-agent control is reviewed. Different approaches for multi-agent control, estimation, and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective. Attention is paid to the design of multi-agent systems via Laplacian dynamics, as well as the role of the graph Laplacian spectrum, the challenges of unbalanced digraphs, and consensus-based estimation of graph statistics. Some emergent issues, e.g., distributed optimization, distributed average tracking, and distributed network games, are also reported, which have witnessed extensive development recently. There are over 200 references listed, mostly to recent contributions.