VedantDave/sac_ae_if
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Denis Yarats 2020-05-02 21:46:01 -04:00 committed by GitHub
parent a86c6dfa82
commit 27643e916d
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 12 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
README.md
View File

@ -8,6 +8,18 @@ This is PyTorch implementation of SAC+AE from
[[Paper]](https://arxiv.org/abs/1910.01741) [[Webpage]](https://sites.google.com/view/sac-ae/home) [[Paper]](https://arxiv.org/abs/1910.01741) [[Webpage]](https://sites.google.com/view/sac-ae/home)
## Citation
If you use this repo in your research, please consider citing the paper as follows
```
@article{yarats2019improving,
title={Improving Sample Efficiency in Model-Free Reinforcement Learning from Images},
author={Denis Yarats and Amy Zhang and Ilya Kostrikov and Brandon Amos and Joelle Pineau and Rob Fergus},
year={2019},
eprint={1910.01741},
archivePrefix={arXiv}
}
```
## Requirements ## Requirements
We assume you have access to a gpu that can run CUDA 9.2. Then, the simplest way to install all required dependencies is to create an anaconda environment by running: We assume you have access to a gpu that can run CUDA 9.2. Then, the simplest way to install all required dependencies is to create an anaconda environment by running:
``` ```