Real-time Decision Making in Networked Dynamical Systems: Algorithms, Fundamental limits, and Applications
Seminar: EE: CS: EECS Seminars | February 13 | 4-5 p.m. | Soda Hall, HP Auditorium (306)
Na Li, Thomas D. Cabot Associate Professor of Electrical Engineering and Applied Mathematics, Harvard University
Recent radical evolution in distributed sensing, computation, communication, and actuation has fostered the emergence of cyber-physical networked systems, across a broad spectrum of engineering and societal fields. Many challenges arise in shaping the network collective behavior through coordinating individual components, such as the large scale of the network, limited communication, inherent uncertainties, and complex intertwined physics and human interactions. In this talk, I will present our recent progress in formally advancing the systematic design of real-time decision making in networked systems, focusing on the challenges raised by uncertainties from two aspects. One is caused by unknown system dynamics and the other is caused by an volatile external environment. We firstly present our recently developed scalable multiagent reinforcement learning algorithms which only use local sensing and communication yet learn nearly-optimal localized policies for the global network. Then we present our online optimal control algorithms with time-varying convex cost functions and rigorously show how to use prediction effectively to reach a nearly-optimal online performance with fast computation. In the end, I will briefly present our other work as well as some real-world system tests and implementations.
Bio: Na Li is a Thomas D. Cabot associate professor in Electrical Engineering and Applied Mathematics of the School of Engineering and Applied Sciences at Harvard University. She received her Bachelor degree in Mathematics from Zhejiang University in 2007 and Ph.D. degree in Control and Dynamical systems from California Institute of Technology in 2013. She was a postdoctoral associate of the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology 2013-2014. She has joined Harvard University since 2014. Her research lies in distributed optimization and control of cyber-physical networked systems. She serves as an associate editor for IEEE transactions on automatic control and systems & control letters and has been in the organizing committees for various conferences. She received NSF career award (2016), AFSOR Young Investigator Award (2017), ONR Young Investigator Award(2019), Donald P. Eckman Award (2019), Harvard PSE Accelerator Award (2017), along with some other awards.