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

  • Authors: Hai Cao, Shaoming Hu, Junju Du, Xu Chen, Shuqi Liu, Shuai Feng, Bo Zhang, Yuchen Jiang

Hai Cao et al 2025 The Astronomical Journal 170 .

  • Provider: AAS Journals

Caption: Figure 1.

Flow scheme of astronomical observation scheduling. Using the features derived from preprocessing the requirements as inputs, the pointer network generates the target’s probability distribution, and an observation plan is created by successively selecting targets.

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