REINFORCE (Vanilla Policy Gradient VPG) Algorithm Explained | Deep Reinforcement Learning

Ғылым және технология

Whiteboard walkthru and explanation of the REINFORCE Policy Gradient Deep Reinforcement Learning algorithm.
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Пікірлер: 7

  • @johnnycode
    @johnnycode2 ай бұрын

    Let me know if you want the code walkthru and demo.

  • @peterhpchen

    @peterhpchen

    28 күн бұрын

    Where is the code?

  • @johnnycode

    @johnnycode

    27 күн бұрын

    @@peterhpchen Here you go github.com/johnnycode8/gym_solutions/blob/main/cliff_walking_reinforce.py

  • @kimiochang
    @kimiochang2 ай бұрын

    Thanks for the good work. I am still practicing the FrozenLake DQL+CNN and wonder how to train the model on CUDA as the training time keeps increasing.

  • @johnnycode

    @johnnycode

    2 ай бұрын

    Thank you for the continual support, Andy! Here are some general guidelines on using CUDA: # First, make sure you have CUDA installed properly and is supported by your GPU device = 'cuda' if torch.cuda.is_available() else 'cpu' print(device) # Then, anywhere that uses the network should be sent to CUDA, for example: DQN(....).to(device) # Also, anywhere that deals with Tensors should be sent to CUDA, for example: torch.FloatTensor(...).to(device) torch.IntTensor(...).to(device) Note that when you run your code and Pytorch complains that not everything is on the same device, it means you didn't send something to CUDA using "to(device)".

  • @kimiochang

    @kimiochang

    2 ай бұрын

    @@johnnycode thanks a lot for the help. And It works!

  • @johnnycode

    @johnnycode

    2 ай бұрын

    @@kimiochangThat’s great 👍

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