CropGym: a Reinforcement Learning Environment for Crop Management

• URL: http://arxiv.org/abs/2104.04326v1
• Date: Fri, 9 Apr 2021 12:17:26 GMT
• Title: CropGym: a Reinforcement Learning Environment for Crop Management
• Authors: Hiske Overweg, Herman N.C. Berghuijs, Ioannis N. Athanasiadis
• Abstract summary: We implement an OpenAI Gym environment where a reinforcement learning agent can learn fertilization management policies. In our environment, an agent trained with the Proximal Policy Optimization algorithm is more successful at reducing environmental impacts than the other baseline agents.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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