Duration: 1 hour Participants: 15 people This lecture introduces Reinforcement Learning (RL) in the context of Agent-Based Modeling (ABM). It explores how RL can be used to train intelligent agents that operate within an ABM, making them adaptive and decision-driven […]
Duration: 1 hour Participants: 30 people This recorded seminar delves into the application of crop hybrid modeling in agriculture. It delved into the pros and cons of each approach, highlighting the potential of combining them to address complex agricultural challenges. […]
Duration: 1 hour Participants: 15 people This presentation delves into the application of Digital Twin technology and AI in Smart Droplets, specifically focusing on WP3. The presentation highlights three key components: a robust data management platform, a powerful digital twin […]
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 […]
Duration: 2 hours Participants: 20 people A seminar targeted towards Agricultural researchers and students, where we disseminate the methods of Reinforcement learning as a tool for smart and adaptive decision making for farm management. Presentation: Download Code: Download (.zip)
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 […]
