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Materials for Deep RL seminars.

Deep RL

Seminars that accompany course CS294 at Berkeley.

  1. Intro to RL [presentation] [assignment]
    • Assignment - MNIST PyTorch
    • Example - CartPole Imitation Learning
    • Example - PyTorch Dynamic Batching
  2. Imitation learning and policy gradient theorem [presentation]
  3. Policy gradient and Actor-Critic algorithm [presentation][assignment]
  4. Model-based RL [presentation]
  5. Deterministic policy gradient [presentation] and multi-armed bandits [presentation]
  6. Inverse RL [presentation]
  7. Advanced Policy Gradient [presentation]