# pytorch-ddpg

**Repository Path**: cmy_program/pytorch-ddpg

## Basic Information

- **Project Name**: pytorch-ddpg
- **Description**: Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2021-12-10
- **Last Updated**: 2022-09-01

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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Deep Deterministic Policy Gradient on PyTorch
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Overview
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The is the implementation of `Deep Deterministic Policy Gradient <https://arxiv.org/abs/1509.02971>`_ (DDPG) using `PyTorch <https://github.com/pytorch/pytorch>`_. Part of the utilities functions such as replay buffer and random process are from `keras-rl <https://github.com/matthiasplappert/keras-rl>`_ repo. Contributes are very welcome.

Dependencies
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* Python 3.4
* PyTorch 0.1.9 
* `OpenAI Gym <https://github.com/openai/gym>`_

Run
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* Training : results of two environment and their training curves:

	* Pendulum-v0

	.. code-block:: console

	    $ ./main.py --debug

	.. image:: output/Pendulum-v0-run0/validate_reward.png
	    :width: 800px
	    :align: left
	    :height: 600px
	    :alt: alternate text

	* MountainCarContinuous-v0

	.. code-block:: console

	    $ ./main.py --env MountainCarContinuous-v0 --validate_episodes 100 --max_episode_length 2500 --ou_sigma 0.5 --debug

	.. image:: output/MountainCarContinuous-v0-run0/validate_reward.png
	    :width: 800px
	    :align: left
	    :height: 600px
	    :alt: alternate text

* Testing :

.. code-block:: console

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

TODO
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