# Stored Embeddings for Efficient Reinforcement Learning (SEER)

Official codebase for Atari experiments in Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. This codebase was originally forked from Kaixhin's [Rainbow](https://github.com/Kaixhin/Rainbow). 


## BibTex

```
```

## Installation 

All of the dependencies are in the `conda_env.yml` file. They can be installed manually or with the following command:

```
conda env create -f conda_env.yml
```

## Instructions
See instructions in Kaixhin's [Rainbow](https://github.com/Kaixhin/Rainbow). Additional hyperparameters are steps_until_freeze. Example scripts for using large replay buffers (run_lb_alien.sh) and small replay buffers (run_sb_alien.sh) can be found in the scripts folder.
