In this talk I will present an overview of some of the past and current lines of research in reinforcement learning (RL), as well as some of the challenges that research in this area has faced in the last decades. I will describe a range of recent results that may bring significant advances on some of these fundamental research challenges, and yet rely on the “simplest” optimization approach – gradient search. The ultimate goal of this talk is to provide a high-level perception of RL while hint on current active avenues of research in this area.
Gradient Approaches to Reinforcement Learning
May 25, 2010
1:00 pm