Projects per year
Abstract
Nitrogen fertilizers have a detrimental effect on the environment, which can be reduced by optimizing fertilizer management strategies. We implement an OpenAI
Gym environment where a reinforcement learning agent can learn fertilization
management policies using process-based crop growth models and identify policies with reduced environmental impact. In our environment, an agent trained
with the Proximal Policy Optimization algorithm is more successful at reducing
environmental impacts than the other baseline agents we present.
Gym environment where a reinforcement learning agent can learn fertilization
management policies using process-based crop growth models and identify policies with reduced environmental impact. In our environment, an agent trained
with the Proximal Policy Optimization algorithm is more successful at reducing
environmental impacts than the other baseline agents we present.
Original language | English |
---|---|
Publisher | arXiv |
Number of pages | 8 |
Publication status | Published - May 2021 |
Fingerprint
Dive into the research topics of 'CropGym: a Reinforcement Learning Environment for Crop Management'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Reinforcement learning in Digital Future Farm
Overweg, H. (PI) & Athanasiadis, I. (Project Leader)
1/11/20 → 30/09/21
Project: PostDoc