An implementation of the Normalized Advantage Function Reinforcement Learning Algorithm with Prioritized Experience Replay
Project description
PER-NAF
An implementation of the Normalized Advantage Function Reinforcement Learning Algorithm with Prioritized Experience Replay
Summary
- The original paper of this code is: https://arxiv.org/abs/1509.02971
- The code is mainly based on: https://github.com/carpedm20/NAF-tensorflow/
- Additionally I added the prioritized experience replay: https://arxiv.org/abs/1511.05952
- Using the OpenAI baseline implementation: https://github.com/openai/baselines/blob/master/baselines/deepq/replay_buffer.py
Thanks openAI and Kim!
Some Advices from experience in RL
- Normalize the state and action space as well as the reward is a good practice
- Visualise as much as possible to get an intuition about the method as possible bugs
- If it does not make sense it is a bug with very high probability
Coding makes happy
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