Semantic Scholar Open Access 2020 3212 sitasi

Reinforcement learning

F. Wörgötter B. Porr

Lihat Sumber DOI

Abstrak

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.

Topik & Kata Kunci

Computer Science Physics

Penulis (2)

F. Wörgötter

B. Porr

Format Sitasi

APA MLA BibTeX

Wörgötter, F., Porr, B. (2020). Reinforcement learning. https://doi.org/10.4249/scholarpedia.1448

Akses Cepat

Lihat di Sumber doi.org/10.4249/scholarpedia.1448

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 3212×
Sumber Database: Semantic Scholar
DOI: 10.4249/scholarpedia.1448
Akses: Open Access ✓