# pytorch-REINFORCE

**Repository Path**: ctpaaa/pytorch-REINFORCE

## Basic Information

- **Project Name**: pytorch-REINFORCE
- **Description**: PyTorch Implementation of REINFORCE for both discrete & continuous control
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-03-31
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# PyTorch REINFORCE

<img src="assets/algo.png" width="800"> 

PyTorch implementation of REINFORCE.     
This repo supports both **continuous** and **discrete** environments in OpenAI gym. 


## Requirement
- python 2.7
- PyTorch
- OpenAI gym
- Mujoco (optional)


## Run
Use the default hyperparameters. *(Program will detect whether the environment is continuous or discrete)*

```
python main.py --env_name [name of environment]
```

## Experiment results
### continuous: InvertedPendulum-v1

<img src="assets/InvertedPendulum-v1.png" width="800">

### discrete: CartPole-v0

<img src="assets/CartPole-v0.png" width="800">

## Reference
- [pytorch example](https://github.com/pytorch/examples/blob/master/reinforcement_learning/reinforce.py)