CropGym: a Reinforcement Learning Environment for Crop Management
CropGym is a highly configurable Python Gymnasium environment to conduct Reinforcement Learning (RL) research for crop management. CropGym is built around PCSE, a well established python library that includes implementations of a variety of crop simulation models. CropGym follows standard gym conventions and enables daily interactions between an RL agent and a crop model.
Installation
Examples
Use Cases
Citing CropGym
If you use CropGym in your publications, please cite us following this Bibtex entry
@article{cropgym,
title={Nitrogen management with reinforcement learning and crop growth models},
volume={2},
DOI={10.1017/eds.2023.28},
journal={Environmental Data Science},
publisher={Cambridge University Press},
author={Kallenberg, Michiel G.J. and Overweg, Hiske and van Bree, Ron and Athanasiadis, Ioannis N.},
year={2023},
pages={e34}
}