# Stored Embeddings for Efficient Reinforcement Learning (SEER)

Official codebase for DeepMind Control Suite experiments in Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. This codebase was originally forked from [RAD](https://github.com/MishaLaskin/rad). 


## BibTex

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## 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 [RAD](https://github.com/MishaLaskin/rad). Additional hyperparameters are steps_until_freeze and num_copies. Example scripts for using large replay buffers (run_lb_cartpole.sh) and small replay buffers (run_sb_cartpole.sh) can be found in the scripts folder.
