✉news ScienceSpace Policy first seen 4 d ago, last 3 d ago, peak #3
New Reinforcement Learning Tool Aims to Streamline Ariel Telescope Scheduling
Original: aRieL – Reinforcement Learning For The Ariel Space Telescope Scheduling
Researchers have introduced aRieL, a reinforcement learning system designed to handle scheduling for ESA's Ariel space telescope, which will study the atmospheres of exoplanets. Automating the observation schedule of a space telescope is a complex optimisation problem, and applying machine learning to it is drawing attention from the astronomy and space policy communities.
Why now: Interest in AI tools being applied to major space missions like ESA's Ariel exoplanet telescope.
Evidence
- aRieL – Reinforcement Learning For The Ariel Space Telescope Scheduling · Astrobiology Web
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