The Research Centre for Machine Learning (RCML) at City is pleased to announce the seminar by Dr. Lucian Busoniu – associate professor with the Department of Automation at the Technical University of Cluj-Napoca.
Please find below the details of the talk:
Venue: AG21 (College Building)
Date & Time: Jun 30, 2016 (12:00-13:00)
Title: Planning Methods for Near-Optimal Nonlinear Control
Abstract: We propose an optimistic planning method to search for near-optimal sequences of actions in discrete-time, infinite-horizon optimal control problems with discounted rewards. The dynamics are nonlinear, while the action is continuous and lies in a bounded interval. The method works like model-based predictive control, but exploits insights from bandit theory in reinforcement learning to run the search. Specifically, it iteratively refines adaptive-dimensionality hyperboxes, always choosing an optimistic box with the largest upper bound on the rewards. Under certain Lipschitz conditions on the dynamics and rewards, a guaranteed near-optimality bound is obtained as a function of the computation invested. We also give an empirical extension that does not require knowing the Lipschitz constants, and works much better in experiments, strongly indicating that such a method is the best next step.
Speaker Bio: Lucian Busoniu received the Ph.D. degree (cum laude) from the Delft University of Technology, the Netherlands, in 2009. He is an associate professor with the Department of Automation at the Technical University of Cluj-Napoca, and has previously held research positions in the Netherlands and France. His research interests include planning for nonlinear optimal control, reinforcement learning and approximate dynamic programming, multiagent systems, and robotics. He received the 2009 Andrew P. Sage Award for the best paper in the IEEE Transactions on Systems, Man, and Cybernetics.