This is the official implementation of NeurIPS 2022 paper Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning. The released code only contains the Chemistry environment modified from this repo.
The code is tested with Ubuntu 20.04 and Python 3.8.
# clone the code
git clone https://github.com/GilgameshD/GRADER.git
cd GRADER
# create conda environment
conda create -n grader python=3.8
conda activate grader
# install dependency
pip install -r requirement.txtRun the following script to train and test agents under different settings.
# mode - [IID/OOD-S]: environment type
# grader_model - [full/causal/gnn/mlp]: model type
# graph - [collider/chain/full/jungle]: groundtruth graph used in chemistry environment
# exp_name: name of the folder to save results
# one example of training GRADER in IID setting
python train_agent.py --mode IID --grader_model causal --graph chain --exp_name test