Comments (2)
I am guessing, by this question, you are referring to vanilla-A3C which was adapted from universe-starter-agent. You would have to train on atari with the relevant wrappers I have provided in env_wrapper.py
. I guess I was able to achieve similar performance as A3C paper corresponding to unshared-RMSprop with similar hyper-parameters used in the A3C paper.
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Closing this issue as of now. Feel free to reopen if needed!
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Related Issues (20)
- Use this model with demo frames
- 安装报错
- a GAN idea HOT 1
- Feature normalization ?
- Question: I want to run a single worker HOT 2
- Tryinf to run simple atari pong HOT 1
- Convergence without LSTM
- Inconsistent actions between train and inference on Mario
- Questions about training
- Tried to run demo.py got syntax error HOT 3
- Generate maze code
- Could the algorithm be used on reinforced learning algorithms with experience reply?
- extrinsic and intrinsic combination HOT 1
- Failed to build doom-py HOT 2
- RuntimeError: go_vncdriver must be imported before tensorflow
- Tensor Board Version
- models.tar.gz cannot be downloaded HOT 3
- Update Code to Tensorflow 2.0
- What is the compatible python version?
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