https://github.com/khushhallchandra/pytorch-rl
Pytorch Implementation of RL algorithms
https://github.com/khushhallchandra/pytorch-rl
artificial-intelligence ddpg deep-learning dqn openai-gym python pytorch reinforcement-learning reinforcement-learning-algorithms rl-agents
Last synced: about 1 month ago
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Pytorch Implementation of RL algorithms
- Host: GitHub
- URL: https://github.com/khushhallchandra/pytorch-rl
- Owner: khushhallchandra
- License: mit
- Created: 2018-01-07T13:30:09.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-02-26T12:12:59.000Z (over 7 years ago)
- Last Synced: 2025-08-31T12:52:38.031Z (about 1 month ago)
- Topics: artificial-intelligence, ddpg, deep-learning, dqn, openai-gym, python, pytorch, reinforcement-learning, reinforcement-learning-algorithms, rl-agents
- Language: Python
- Homepage:
- Size: 1.25 MB
- Stars: 15
- Watchers: 5
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pytorch-rl
## DDPG| | Un-Trained | Trained |
|----|--------------|------|
|DDPG| |
|DQN| | 
|CEM| | pytorch-rl is a python package based on pytorch library which aims to build standard deep reinforcement learning agent for the user to build various algorithms around it. pytorch-rl also includes some of the state-of-the-art implementations of popular deep reinforcement learning.
## Installation
pytorch-rl can be easily installed using `pip` as follows:
```
pip install pytorch-rl
```
This code currently uses python 2.7 and is compatible with both CPU and GPU (cuda 8.0).
## Usage
All the algorithmic implementations of a RL agent lies in the `rl` repository. While the RL agent (say DDPG) can be imported as follows,
```
from rl.agents import DDPGAgent
```
The standard DNN model associated with particular agent can be imported as follows
```
from rl.models.ddpg import ActorNetwork, CriticNetwork
```
Similarly, to run one of our RL agents( say DDPG) on a standard environment, simply run the following command
```
python examples/ddpg_pendulum.py
```
```
python examples/ddpg_cartpole.py
```
Agents implemeted currently
- [x] DDPG
- [x] DDQN
- [x] Duel DQN
- [x] CEM
- [x] PPO(needs to be tested)
- [x] ACKTR(needs to be tested)
- [x] A2C(needs to be tested)