With an influx of many new communication and computation technologies, many systems that once existed in isolation now interact and form the basis of large multi-agent systems (e.g., fleets of drones/robots or human drivers with live-traffic routing apps). Though this advance in scale and connectivity offers many opportunities, a major challenge comes from the fact that the emergent system behavior induced by many local decisions need not be optimal. As a method to elicit greater coordination, we can design how individual system components behave, or we can design how they communicate with one another. I will discuss several ways in which information-communication channels can be exploited as a method to control overall system behavior. Particularly, I will present a game-theoretic model for distributed decision-making and demonstrate the possible benefits and costs of increasing communication in terms of gain/loss to equilibrium efficiency and solution complexity.
Bryce L. Ferguson is a PhD candidate in the Electrical and Computer Engineering Department at the University of California, Santa Barbara. Bryce received his BS and MS in Electrical Engineering from the University of California, Santa Barbara in June 2018 and March 2020, respectively, and his A.A. in Mathematics from Santa Rosa Junior College in 2016. He was named a 2022 CPS Rising Star and was a finalist for the Best Student Paper Award at the 2020 American Controls Conference. Bryce's research interests focus on using game theoretic methods for describing and controlling both social and engineered multi-agent systems.