A multiagent system can be characterized by a collection of interacting subsystems each making local decisions in response to local information. There are numerous examples of multiagent systems spanning both the engineering and social sciences, e.g., wind farms, surveillance systems, and transportation networks. Regardless of the specific domain, the primary goal in such systems is to design admissible mechanisms for coordinating the behavior of the individual subsystems to ensure that the emergent collective behavior is desirable with respect to a system-level objective.
Intellectual Merit
The overarching goal of this project is to develop game-theoretic methodologies for multiagent coordination with broad applicability to both social and engineering systems. In the context of social multiagent systems, this project will focus on the derivation of optimal mechanisms for coordinating the collective behavior in situations where the society's sensitivity to such mechanisms is unknown, e.g., taxation mechanisms on traffic networks. In the context of engineering multiagent systems, this project will focus on the derivation of (i) distributed control algorithms that guarantee that the multiagent systems exhibits the optimal correlated behavior and (ii) fundamental relationships pertaining to how informational patterns impact achievable performance guarantees in multiagent systems.
Broader Impacts
A central goal on this project involves promoting the general understanding of multiagent systems to the engineering community and beyond. Undoubtedly, engineers will be responsible for the design of a wide array of multiagent systems with examples spanning all aspects of society. Successfully controlling such ?complex? systems requires that engineers be multi-disciplinary with a strong proficiency in both the engineering and social sciences. This project will seek to achieve this goal through direct interactions with K-12 students, public lectures, dissemination of course material at the intersection of social and engineering sciences, and direct interactions with industry to illustrate the applicability of the developed methodologies.
