Abstract

The successful deployment of complex multi-agent systems requires well-designed, agent-level control strategies that guarantee system-level dynamics to be robust to disturbance and adaptive in the face of changes in the environment. In applications, such as mobile sensor networks, limitations on individual agents in sensing, communication, and computation create a further challenge. However, system-level dynamics that are both robust and adaptive are observed in animal groups, from bird flocks to fish schools, despite limitations on individual animals in sensing, communication, and computation. To better understand and leverage the parallels between networks in nature and design, a principled examination of collective dynamics is warranted. I will describe an analytical framework based on nonlinear dynamical systems theory for the realization of collective decision-making that allows for the rigorous study of the mechanisms of observed collective animal behavior together with the design of distributed strategies for collective dynamics with provable performance.