Matthieu Geist (Google Brain)
Date: Monday 19 October 7 PM – 9 PM UTC
Many recent efficient deep reinforcement learning algorithms make use of some sort of regularization. This tutorial will review these approaches through the lens of regularized approximate dynamic programming, which allows connecting the different algorithms and explains theoretically why regularization works.