Playlist: 25 videos

Deep Reinforcement Learning

0:30:32

Munchausen Reinforcement Learning

Matthieu Geist (Google)
https://simons.berkeley.edu/talks/tbd-208
Deep Reinforcement Learning
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0:28:42

Adaptive Approximate Policy Iteration

Nevena Lazic (DeepMind)
https://simons.berkeley.edu/talks/tbd-213
Deep Reinforcement Learning
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0:29:42

Stabilizing Q-learning with Weighted Bellman Losses

Pieter Abbeel (UC Berkeley)
https://simons.berkeley.edu/talks/tbd-218
Deep Reinforcement Learning
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0:33:43

Generalizing the Projected Bellman Error Objective for Nonlinear Value Estimation

Martha White (University of Alberta)
https://simons.berkeley.edu/talks/tbd-223
Deep Reinforcement Learning
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0:42:50

Discussion: Optimization

Moderator: Gergely Neu (UPF)
https://simons.berkeley.edu/talks/tbd-228
Deep Reinforcement Learning
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0:31:22

Language as a Scaffold for Reinforcement Learning

Jacob Andreas (MIT)
https://simons.berkeley.edu/talks/tbd-209
Deep Reinforcement Learning
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0:28:29

Invariant Prediction for Generalization in Reinforcement Learning

Clare Lyle (University of Oxford)
https://simons.berkeley.edu/talks/tbd-212
Deep Reinforcement Learning
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0:29:34

Exploiting Latent Structure and Bisimulation Metrics for Better Generalization

Amy Zhang (McGill University, Mila Institute, Facebook AI Research)
https://simons.berkeley.edu/talks/tbd-219
Deep Reinforcement Learning
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0:31:56

Fast Reinforcement Learning With Generalized Policy Updates

Doina Precup (McGill Univeristy & MILA / DeepMind)
https://simons.berkeley.edu/talks/tbd-224
Deep Reinforcement Learning
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0:43:39

Policy Gradients Methods, Neural Policy Classes, and Distribution Shift

Sham Kakade (University of Washington)
https://simons.berkeley.edu/talks/tbd-227
Deep Reinforcement Learning
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