“Distributed Estimation, Objective Reconstruction, and Efficient Control of Multiagent Systems”
Wednesday, Nov. 29 at 3:00pm
LAR 229

Abstract

Inspired by human interactions with cyber-physical agents, Dr. Lian’s research focuses on distributed estimation, objective identification, and intelligent control. His presentation highlights the development of a distributed Kalman consensus filter for estimating multiple moving targets. This filter accounts for limited sensor sensing ranges, showcasing faster convergence and enhanced robustness. Dr. Lian’s research extends to learning mechanisms that marry reinforcement learning and inverse optimal control, designing optimal decision mechanisms from demonstrated behavior. The mechanisms address objective function reconstruction and imitation learning in diverse scenarios. Moreover, he will introduce novel learning and control strategies, tailored for larger, complex networked systems, effectively managing computational complexity while retaining essential dynamic information and reducing required learning data.

Biography

Dr. Bosen Lian is currently an assistant professor with the Electrical and Computer Engineering Department at Auburn University. Prior to that, Dr. Lian was an adjunct professor at the Electrical Engineering Department of University of Texas at Arlington (UTA), and a postdoctoral research Associate at UTA Research Institute. He serves as an associate editor for IEEE Transactions on Neural Networks and Learning Systems and Transactions of the Institute of Measurement and Control. His impactful research has been recognized in high-impact journals such as IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, etc. His research interests center around (inverse) reinforcement learning, distributed estimation, and distributed control.