IEEE Distinguished Lecture Improved reinforcement learning with applications in robotics, games, and quantum engineering Daoyi Dong, Ph.D. ARC Future Fellow and Professor, IEEE Fellow School of Engineering, Australian National University Place: Room ECE 202, NJIT, Newark, NJ ZOOM (for online attendees): https://montclair.zoom.us/j/2423669227 Time: 10:30 am -12:00 pm, Monday, April 22, 2024 (Eastern Time) Host: MengChu Zhou, Ph.D. & Dist. Professor, NJIT and Weitian Wang, Ph.D. & Associate Professor, Montclair State University ABSTRACT Reinforcement learning (RL) addresses the problem of how an autonomous active agent can learn to approximate an optimal behavioral strategy while interacting with its environment. It has been widely applied in various areas including artificial intelligence, control engineering, operations research, and robotics. In this lecture, I will introduce several improved reinforcement learning algorithms including incremental reinforcement learning, quantum reinforcement learning, and quantum-inspired deep reinforcement learning. I will also demonstrate several applications of these improved reinforcement learning algorithms in robotics, games, and quantum engineering. Dr. Daoyi Dong (S’05-M’06-SM’11-F’23) is currently a Professor at the Australian National University. Before moving to the Australian National University, he had worked at the University of New South Wales, Australia for 15 years. He was with the Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Zhejiang University. He had/has visiting positions at Princeton University, USA, RIKEN, Japan, the University of Hong Kong, Hong Kong, University of Duisburg-Essen, Germany, the University of Sydney, and the University of Melbourne, Australia. He received a B.E. degree in automatic control and a Ph.D. degree in engineering from the University of Science and Technology of China, in 2001 and 2006, respectively. His research interests include machine learning, quantum control, system identification, and renewable energy. He has published over 120 journal papers in leading journals including IEEE Transactions (40+), Nature Human Behaviour, Physical Review Letters, and Automatica, and more than 60 conference papers. He was awarded an ACA Temasek Young Educator Award by the Asian Control Association and is a recipient of a Future Fellowship, an International Collaboration Award, a Discovery International Award and an Australian Post-Doctoral Fellowship from the Australian Research Council, a Humboldt Research Fellowship from the Alexander von Humboldt Foundation in Germany, and a Scientia Fellowship from the University of New South Wales. Prof Dong was elevated as an IEEE Fellow for contributions to quantum systems control and reinforcement learning. He currently serves as an Associate Editor of IEEE Transactions on Cybernetics and IEEE/CAA Journal of Automatica Sinica. He was an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, a Technical Editor of IEEE/ASME Transactions on Mechatronics and a Guest Editor of Annual Reviews in Control. He is a Member-at-Large of Board of Governors, and was the Associate Vice President for Conferences & Meetings, IEEE Systems, Man and Cybernetics Society. He was the founding chair of IEEE Control Systems Society ACT/NSW Joint Chapter, the founding chair of IEEE Systems, Man and Cybernetics Society ACT Chapter, the founding chair of Technical Committee on Quantum Computing, Systems and Control, IEEE Control Systems Society, and the founding chair of Technical Committee on Quantum Cybernetics, IEEE Systems, Man and Cybernetics Society. He has also served as General Chair or Program Chair for several international conferences, and as a member of Fellow Evaluating Committee of IEEE Technology and Engineering Management Society. Room ECE 202, NJIT, Newark, New Jersey, United States, 07102, Virtual: https://events.vtools.ieee.org/m/413238
