ESE Seminar: “Demystifying (Deep) Reinforcement Learning: The Optimist, The Pessimist, and Their Provable Efficiency”
Zoom - Email ESE for Link jbatter@seas.upenn.eduCoupled with powerful function approximators such as deep neural networks, reinforcement learning (RL) achieves tremendous empirical successes. However, its theoretical understandings lag behind. In particular, it remains unclear how to provably attain the optimal policy with a finite regret or sample complexity. In this talk, we will present the two sides of the same coin, […]