A validation and traceability framework using data checks, logical consistency, constraint verification, and atomic reasoning units to improve reliability of AI telescope scheduling decisions.
Deep Reinforcement Learning for Efficient Scheduling of Ground-based Astronomical Observations.Astron
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Multi-Level Validation and Traceability Framework for AI-Generated Telescope Scheduling Decisions
A validation and traceability framework using data checks, logical consistency, constraint verification, and atomic reasoning units to improve reliability of AI telescope scheduling decisions.