duzx16 / pytorch-ddpg

Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

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Deep Deterministic Policy Gradient on PyTorch
Overview
======

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
Run
======
  • 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

image

width

800px

align

left

height

600px

alt

alternate text

  • Testing :

$ ./main.py --mode test --debug

TODO

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Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

License:Apache License 2.0


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