In the Pacific Northwest, billions of dollars hinge on knowing when a grapevine will bloom. A research team from Oregon State University and Washington State University, funded by a National Science Foundation grant through the AgAID AI Institute, is bringing reinforcement learning and hybrid modeling to that forecasting problem.
The foundation is WOFOSTGym, a crop management simulator built atop the decades-old WOFOST (WOrld FOod STudies), an open-source, mechanistic crop growth simulation model. Published at the 2025 Reinforcement Learning Conference, where it won a best paper award for reinforcement learning applications, WOFOSTGym lets AI researchers train agents on realistic crop management problems without agricultural expertise.
