Deep Reinforcement Learning in the Real World - Sergey Levine

Deep Reinforcement Learning in the Real World - Sergey Levine

Institute for Advanced Study via YouTube Direct link

Off-policy model-free learning

6 of 19

6 of 19

Off-policy model-free learning

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Deep Reinforcement Learning in the Real World - Sergey Levine

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  1. 1 Intro
  2. 2 Deep learning helps us handle unstructured environments
  3. 3 Reinforcement learning provides a formalism for behavior
  4. 4 RL has a big problem
  5. 5 Off-policy RL with large datasets
  6. 6 Off-policy model-free learning
  7. 7 How to solve for the Q-function?
  8. 8 QT-Opt: off-policy Q-learning at scale
  9. 9 Grasping with QT-Opt
  10. 10 Emergent grasping strategies
  11. 11 So what's the problem?
  12. 12 How to stop training on garbage?
  13. 13 How well does it work?
  14. 14 Off-policy model-based reinforcement learning
  15. 15 High-level algorithm outline
  16. 16 Model-based RL for dexterous manipulation
  17. 17 Q-Functions (can) learn models
  18. 18 Temporal difference models
  19. 19 Optimizing over valid states

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