Automated Synthesis of Multi-Agent Control

Abstract : We have been pursuing a synthetic approach to studying the problem of controlling complex multi-robot systems by simultaneously developing a theory and testing it on complex domains consisting physical mobile robots. This process allows us to evaluate, improve, and further develop our theory, while producing a set of useful software and hardware applications. Our approach is behavior-based; the robots use a set of behaviors (parametric, goal-achieving control laws) as a substrate for control, representation, and learning. This approach scales well to large multi-robot systems, and enables us to flexibly explore complex problems such as the coordination of decentralized groups and learning in such distributed systems.