Article

Tabular Reinforcement Learning for Reward Robust, Explainable Crop Rotation Policies Matching Deep Reinforcement Learning Performance

2024-10-30

Abstract excerpt

Digital Twins’ design frequently incorporates machine learning and, more recently, deep reinforcement learning techniques in order to interpret data and forecast future outcomes based on incoming data. However, because neural networks are typically considered a ”black box” model, doubts over the reliability of the output from deep learning models continue. In our work, we developed crop rotation policies using exp...

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Literature Corpus work: dde705c0-808c-5fdc-80df-ad93c0ae11da
DOI: 10.20944/preprints202410.2391.v1

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