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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 6.

Comparative visualizations of the scheduled observation plans. The top panel presents the plan simulating manual observations (“Random”), the middle panel displays the results generated using the greedy algorithm (“Greedy”), and the bottom panel shows the observation plan generated by our proposed DRL-based model (“DRL”). The width of the black bars indicates the switch time, while the width of the colored bars indicates the observing time of the task.

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