gym-DSSAT: a crop model turned into a Reinforcement Learning environment

Addressing a real world sequential decision problem with Reinforcement Learning (RL) usually starts with the use of a simulated environment that mimics real conditions. We present a novel open source RL environment for realistic crop management tasks. gym-DSSAT is a gym interface to the Decision Sup...

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Veröffentlicht in:	arXiv.org 2022-09
Hauptverfasser:	Gautron, Romain, Padrón, Emilio J, Preux, Philippe, Bigot, Julien, Maillard, Odalric-Ambrym, Emukpere, David
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Decision support systems Learning Simulation Simulator fidelity Simulators
Online-Zugang:	Volltext
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