Currently there are only the codes for distributional reinforcement learning here. Codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.
Thanks to sungyubkim and Shangtong Zhang!
A lot of my codes references their implementations.
Always up for a chat -- shoot me an email if you'd like to discuss anything!
- pytorch(>=1.0.0)
- gym(=0.10.9)
- numpy
- matplotlib
When your computer's python environment satisfies the above dependencies, you can run the code. For example, enter:
python 4_iqn.py Breakout
on the command line to run the algorithms in the Atari environment. You can change some specific parameters for the algorithms inside the codes.
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Human-level control through deep reinforcement learning(DQN) [Paper] [Code]
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A Distributional Perspective on Reinforcement Learning(C51) [Paper] [Code]
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Distributional Reinforcement Learning with Quantile Regression(QR-DQN) [Paper] [Code]
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Implicit Quantile Networks for Distributional Reinforcement Learning(IQN) [Paper] [Code]
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QUOTA: The Quantile Option Architecture for Reinforcement Learning(QUOTA) [Paper] [Code]