qbx2 / Paac.pytorch
Pytorch implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning https://arxiv.org/abs/1705.04862
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PAAC.pytorch
Pytorch implementation of the PAAC algorithm presented in "Efficient Parallel Methods for Deep Reinforcement Learning". PAAC is the abbreviation of Parallel Advantage Actor-Critic.
Currently, because the PAAC network is not using LSTM, the evaluation result is not very good. I'm working on the LSTM version of PAAC (waiting for a new graphic card due to lack of current gpu's memory.)
The original paper is here: https://arxiv.org/abs/1705.04862
Requirements
PAAC.pytorch requires torch, torchvision, PIL, gym.
Libraries used in this project:
- torch==0.1.12+32e6665
- torchvision==0.1.8
- Pillow==4.1.1
- [email protected]
Result (BreakoutDeterministic-v4 training log)
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