This is modified version for PDERL algorithm.
original repo: https://github.com/crisbodnar/pderl
@inproceedings{bodnar2020proximal,
title={Proximal distilled evolutionary reinforcement learning},
author={Bodnar, Cristian and Day, Ben and Li{\'o}, Pietro},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={34},
number={04},
pages={3283--3290},
year={2020}
}
- update dependency gym to gymnasium
install dependencies:
pip install -r requirements.txt
To run PDERL with proximal mutations and distillation-based crossover use:
python run_pderl.py -env=$ENV_NAME$ -distil -proximal_mut -mut_mag=$MUT_MAG$ -logdir=$LOG_DIR$
To evaluate and visualise a trained model in an environment use:
python play_pderl.py -env=$ENV_NAME$ -model_path=$MODEL_PATH$ -render
'Hopper-v4' \