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Irrigation Scheduling Using model-based Reinforcement Learning for Stochastic Differential Equation control

Water is one of farming’s most precious resources, and at the University of Toronto, Professor Chi-Guhn Lee is determined to use it wisely. His research is creating a decision-support tool based on model-based reinforcement learning to optimize irrigation schedules. By considering weather patterns, crop needs, and ecohydrological conditions, this system will help farmers water their fields at exactly the right time and in the right amount. Pilot testing in two sites in India will show how the technology can improve yields while conserving water — a crucial need in climate-challenged regions.

Canadian PI: Chi-Guhn Lee, Professor, University of Toronto