research
The Agent Used Half the Water
Mimir kept the physical model and actuator limits fixed while letting experience revise contextual guidance.
Summary
Mimir kept the physical model and actuator limits fixed while letting experience revise contextual guidance.
Mimir separates fast repair from slow learning in season-long irrigation control. A deterministic simulator checks and bounds each language-model proposal before execution, while repeated failures become persistent contextual principles without changing the physical model or safety constraints. Under the authors' retrospective evaluator across multiple sites, crops and years, Mimir reported the lowest aggregate control cost among tested references and about 51 percent less irrigation than historical schedule replay; the study does not establish prospective farm performance.
Why it matters
Mimir kept the physical model and actuator limits fixed while letting experience revise contextual guidance.
Limits and context
- Under the authors' retrospective evaluator across multiple sites, crops and years, Mimir reported the lowest aggregate control cost among tested references and about 51 percent less irrigation than historical schedule replay; the study does not establish prospective farm performance.
Key claims
Mimir kept the physical model and actuator limits fixed while letting experience revise contextual guidance.
Qualification: Under the authors' retrospective evaluator across multiple sites, crops and years, Mimir reported the lowest aggregate control cost among tested references and about 51 percent less irrigation than historical schedule replay; the study does not establish prospective farm performance.
Evidence: source-2026-10-03-015
Sources
- arXiv preprint 2610.02038arXiv · primary research
Corrections
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