# Generalized Munchausen RL with Tsallis KL divergence
This is the implementation of  MVIq.

## Setup
If you are using Anaconda, you might want to use virtual environment.

```bash
conda create -n  MVIq python=3.7 -y
conda activate  MVIq
```

You can install Python libraries using pip.

```bash
pip install -r requirements.txt
```

If you're using other than CUDA 10.2, you may need to install PyTorch for the proper version of CUDA. See [instructions](https://pytorch.org/get-started/locally/) for more details.



## Examples
You can train  MVIq on the OpenAI gym environments by:

```
python run_gym.py
```


for algorithms on Atari:
```
python run_atari.py
```

The results are saved in ./data/atari/env_name/alg_name/q/seed/, $q$ denotes different entropic indices.

