Subject: The history, basic theory and method of reinforcement learning

Speaker: Prof. Biao Huang

Time: 10:00am, 24th Nov, 2020

Place: https://meeting.tencent.com/s/dKqElbVOH33r(Tencent Meeting ID: 468 338 961)

Abstract:

Machine learning has progressed rapidly in the past 10 years. Especially in the field of image processing, speech analysis and intelligent technology, machine learning has become an indispensable tool. As one of the core algorithms of machine learning, reinforcement learning has been widely used and achieved a lot of success. From the control point of view, it is also an effective optimal control method based on data and self-learning. This report will introduce the development history, basic theory and method of reinforcement learning.

About the speaker:

Biao Huang received the B.Sc. and M.Sc. degrees in automatic control from Beijing University of Aeronautics and Astronautics, Beijing, China, in 1983 and 1986, respectively, and the Ph.D. degree in process control from the University of Alberta, Edmonton, AB, Canada, in 1997. He joined the University of Alberta in 1997 as an Assistant Professor in the Department of Chemical and Materials Engineering and is currently a Professor, NSERC Industrial Research Chair in Control of Oil Sands Processes, and AITF Industry Chair in Process Control. His research interests include process control, system identification, control performance assessment, Bayesian methods, and state estimation.

Prof. Huang is a Fellow of the Canadian Academy of Engineering and the Chemical Institute of Canada. He is the Editor-in-Chief of Control Engineering Practice, an Associate Editor of Journal of Process Control and Canadian Journal of Chemical Engineering. He is a Fellow of IEEE.