Discussion: Offline Reinforcement Learning

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=eePo73jKIvE


Category:
Discussion
Duration: 40:01
2,194 views
42

Moderator: Pablo Castro (Google)
https://simons.berkeley.edu/talks/tbd-230
Deep Reinforcement Learning



Other Videos By Simons Institute for the Theory of Computing


2020-09-30Generalizing the Projected Bellman Error Objective for Nonlinear Value Estimation
2020-09-30Stabilizing Q-learning with Weighted Bellman Losses
2020-09-30Munchausen Reinforcement Learning
2020-09-30Adaptive Approximate Policy Iteration
2020-09-30On Distance Approximation for Graph Properties
2020-09-29Discussion: Exploration
2020-09-29PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
2020-09-29Temporally-Extended ε-Greedy Exploration
2020-09-29Learning Exploration Strategies with Meta-Reinforcement Learning
2020-09-29Behaviour Suite for Reinforcement Learning
2020-09-28Discussion: Offline Reinforcement Learning
2020-09-28Attacking the Off-Policy Problem With Duality
2020-09-28Offline Deep Reinforcement Learning Algorithms
2020-09-28Learning from the Past Without Great Exploration
2020-09-28MOPO: Model-Based Offline Policy Optimization
2020-09-25Pedagogical Talk: Frameworks for Information-Computation Tradeoffs
2020-09-25Reducibility and Statistical-Computational Gaps from Secret Leakage
2020-09-25Berkeley in the 80s, Episode 4: Andrew Yao
2020-09-25Free Energy Wells and Overlap Gap Property in Sparse PCA
2020-09-25The Overlap Gap Property in Principal Submatrix Recovery
2020-09-24Phase Retrieval in High Dimensions: Statistical and Computational Phase Transitions


Tags:
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Pablo Castro
Deep Reinforcement Learning