The programme.
Develop a greenhouse energy concept through technical design, peer review and scenario analysis. Close with team presentations and research connections.
Wednesday 9 December 2026 · 09:30–17:00 CET · Wageningen
Provisional programme. We’re creating and fine-tuning the sessions. The timetable may change within the official hours; the exact venue will follow.
| Time (CET) | Session |
|---|---|
| –10:00 | Challenge briefing and domain Q&AExplore the greenhouse energy system, its actors and constraints. |
| –11:15 | Team formation and initial designSelect a decision, map existing resources and define the agent’s contribution. |
| –11:30 | Break |
| –12:15 | Peer review and revisionDiscuss feasibility, assumptions and human authority with other teams. |
| –13:00 | Lunch |
| –14:45 | Concept development and scenario analysisRefine the architecture and examine changed conditions, failures and intervention. |
| –15:00 | Break |
| –16:00 | Documentation and presentation preparationConsolidate the concept, its limitations and the next investigation. |
| –17:00 | Team presentations and feedbackPresent the design and discuss its technical and research potential. |
| –17:30 | Research connections and closeOptional · after the official programme Identify complementary expertise and possible follow-up questions. |
Your team’s output
By the end of the day, share a concrete solution concept and a short team presentation. Your concept can take one or more of these forms:
- Conceptual design or Agentic AI architecture
- Agent workflow, integration or human oversight mechanism
- Implementation roadmap and feasibility assessment
- Business impact analysis or systematic testing strategy
- Optional prototype, simulation or working demonstration
Explain the innovation, meaningful use of Agentic AI, feasibility and potential real-world impact. A working system is not required.
The participant briefing will confirm case materials, tool access and arrival details. KasFlex access and support remain to be confirmed. The working language is English.
Find your next
research collaboration.
Join us to develop an idea, meet experts from the field and explore what comes next for agentic AI in greenhouse energy management.