Duration: 2 hours Participants: 15 people The lecture provides an overview of policy approximation in Reinforcement Learning (RL), with a particular emphasis on the use of neural networks. It introduces the concept of policy networks, which learn to map states […]
Duration: 1.5 hours Participants: 30 people This recorded lecture explores the intersection of AI and crop growth modeling. Delivered to a distinguished audience of PhD students and postdoctoral researchers from WU and the University of Florida, the presentation delves into […]
Duration: 2 hours Participants: 30 people A workshop on digital twins hosted by WU aimed at researchers, agronomists and practitioners from around Europe. Three keynote lectures presented and discussed current state-of-the-art implementations of DTs: (1) Towards Digital Twins for Plants: […]
Duration: 0.5 hour Participants: – This presentation showcases student work on a crop management use case, leveraging Reinforcement Learning (RL) and the cropgym package. Students trained an AI agent to optimize fertilization strategies for winter wheat. The RL environment, powered […]
Duration: 1 hour Participants: 10 people The lecture delves into the realm of policy approximation in Reinforcement Learning (RL), specifically focusing on the utilization of neural networks. It explores the concept of policy networks, which learn to map states to […]
Lecturer: Duration: 2 hours Participants: 3 people An Introduction to Reinforcement Learning (RL) and an in-depth dive into the workings of CropGym. Lengthy discussions between (agriculture and artificial intelligence) domain experts was done to find a middle ground in ways […]
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