LM_AG
Jing Wu and collaborators
Open research code for a crop-management decision agent that combines a language model, reinforcement learning and DSSAT crop simulations to choose irrigation and nitrogen-management actions in simulated US crop settings.
QUICK INFO
SOLUTION TYPE
Models, data & tools
TECHNOLOGY CATEGORY
Agents & workflow automation
AREA OF WORK
Agronomy, soil & crop management
ACCESS
Free
DEPLOYMENT
Self-hosted / on-premise
SOURCE REVIEWED
October 6, 2026
What it helps with
- Prototype crop-management agents
- Compare simulated nitrogen and irrigation strategies
- Research language-model crop decision systems
Scope & audience
WHO IT'S FOR
Developer / AI builder · Scientist / researcher
AREA OF WORK
Agronomy, soil & crop management
COMMODITY / SCOPE
Cross-commodity
Access & technical details
ACCESS
Anyone can get it
INTERFACE
Code repository
DEPLOYMENT
You run it yourself
LANGUAGES
English
Featured media
Source information
This listing was compiled from publicly available source material. Verify current details with the provider.
PROVIDER DOCUMENTATION
Reviewed October 2026
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