EGPO
[CoRL 2021] Official implementation of paper "Safe Driving via Expert Guided Policy Optimization".
Install / Use
/learn @decisionforce/EGPOREADME
Expert Guided Policy Optimization (EGPO)
Official implementation of CoRL 2021 paper: Safe Driving via Expert Guided Policy Optimization.
Webpage | Code | Video | Poster | Paper
Installation
# Clone the code to local
git clone https://github.com/decisionforce/EGPO.git
cd EGPO
# Create virtual environment
conda create -n egpo python=3.7
conda activate egpo
# Install basic dependency
pip install -e .
# Now you can run the training script of EGPO.
# If you wish to run other baselines, some extra environmental
# setting is required as follows:
# To run CQL/BC, ray needs to be updated to 1.2.0
pip install ray==1.2.0
# To run GAIL/DAgger, please install GPU-version of torch:
conda install pytorch==1.5.0 torchvision==0.6.0 -c pytorch
conda install condatoolkit==9.2
Training
cd EGPO/training_script/
python train_egpo.py
You can also run other baselines by running the training scripts directly.
You can evaluate the trained agent from EGPO via the following script:
cd EGPO/training_script/
python evaluate_egpo.py # Change CKPT_PATH to your own checkpoint.
Reference
@inproceedings{peng2021safe,
title={Safe Driving via Expert Guided Policy Optimization},
author={Peng, Zhenghao and Li, Quanyi and Liu, Chunxiao and Zhou, Bolei},
booktitle={5th Annual Conference on Robot Learning},
year={2021}
}
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