Reinforcement learning

• URL: http://arxiv.org/abs/2405.10369v1
• Date: Thu, 16 May 2024 18:03:17 GMT
• Title: Reinforcement learning
• Authors: Sarod Yatawatta,
• Abstract summary: 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.
• Score: 0.8702432681310399
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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