This repository includes the implementation of `Environment Generation for Zero-Shot Compositional Reinforcement Learning' by Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi,Manoj Tiwari, Honglak Lee, and Aleksandra Faust. NeurIPS'21.
There are two core components: (i) CoDE, Compositional Design of Environments, and (ii) the gMiniWoB framework. For now, it only hosts the main gMiniWoB implementation. The rest will be added soon.
- Download contents:
svn export https://github.com/google-research/google-research/trunk/compositional_rl
- Create a new directory:
mkdir /path/to/compositional_rl/gwob/bootstrap/
- Download bootstrap files from https://github.com/twbs/bootstrap/releases/download/v4.3.1/bootstrap-4.3.1-dist.zip
- Extract
/path/to/bootstrap/js/bootstrap.min.js
and/path/to/bootstrap/css/bootstrap.min.css
to/path/to/compositional_rl/gwob/bootstrap/
.
- Clone the MiniWoB project:
git clone https://github.com/stanfordnlp/miniwob-plusplus
- Put the whole directory
/path/to/miniwob-plusplus
under/path/to/compositional_rl/gwob/
You should now have three folders /path/to/compositional_rl/gwob/gminiwob/
, /path/to/compositional_rl/gwob/bootstrap/
, and /path/to/compositional_rl/gwob/miniwob-plusplus/
.
- Open
file:///path/to/compositional_rl/gwob/gminiwob/sample_random_website.html
in a browser and click "START". - Each time the "START" button is clicked, this will create a random gMiniWoB website using a subset of primitives available in gMiniWoB.