Deep Deterministic Policy Gradient on PyTorch
Overview
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The is the implementation of Deep Deterministic Policy Gradient (DDPG) using PyTorch. Part of the utilities functions such as replay buffer and random process are from keras-rl repo. Contributes are very welcome.
Dependencies
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* Python 3.4
* PyTorch 0.1.9
OpenAI Gym
Run
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Training : results of two environment and their training curves:
Pendulum-v0
$ ./main.py --debug
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MountainCarContinuous-v0
$ ./main.py --env MountainCarContinuous-v0 --validate_episodes 100 --max_episode_length 2500 --ou_sigma 0.5 --debug
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Testing :
$ ./main.py --mode test --debug
TODO