Deep Reinforcement Learning for Efficient Scheduling of Ground-based Astronomical Observations

Deep Reinforcement Learning for Efficient Scheduling of Ground-based Astronomical Observations

Ground-based astronomical observations face inherent challenges from weather changes, target visibility window constraints, and observational requirements. Enhancing the efficiency and effectiveness of telescope operations has long been a key objective for many observatories because of the high cost...

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Bibliographic Details
Main Authors: Hai Cao, Shaoming Hu, Junju Du, Xu Chen, Shuqi Liu, Shuai Feng, Bo Zhang, Yuchen Jiang
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astronomical Journal
Subjects:
Ground-based astronomy
Observational astronomy
Astronomical techniques
Neural networks
Optical observation
Online Access:https://doi.org/10.3847/1538-3881/ade3dc
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https://doi.org/10.3847/1538-3881/ade3dc

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