Reinforcement learning
<|reference_start|>Reinforcement learning: Observing celestial objects and advancing our scientific knowledge about them involves tedious planning, scheduling, data collection and data post-processing. Many of these operational aspects of astronomy are guided and executed by expert astronomers. Reinforcement learning is a mechanism where we (as humans and astronomers) can teach agents of artificial intelligence to perform some of these tedious tasks. In this paper, we will present a state of the art overview of reinforcement learning and how it can benefit astronomy.<|reference_end|>
@article{yatawatta2024reinforcement,
    title={Reinforcement learning},
    author={Sarod Yatawatta},
    journal={arXiv preprint arXiv:2405.10369},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.10369},
    primaryClass={astro-ph.IM cs.AI cs.LG}
}