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Stable-baselines3: Reliable reinforcement learning implementations.
J. Mach. Learn. Res. 22, accepted (2021)
Stable-Baselines3 provides open-source implementations of deep reinforcement learning (RL) algorithms in Python. The implementations have been benchmarked against reference codebases, and automated unit tests cover 95% of the code. The algorithms follow a consistent interface and are accompanied by extensive documentation, making it simple to train and compare different RL algorithms. Our documentation, examples, and source-code are available at https://github.com/DLR-RM/stable-baselines3.
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2.907
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Baselines ; Open-source ; Python ; Pytorch ; Reinforcement Learning ; Software
Language
english
Publication Year
2021
HGF-reported in Year
2021
ISSN (print) / ISBN
1532-4435
e-ISSN
1533-7928
Quellenangaben
Volume: 22
Publisher
MIT Press
Reviewing status
Peer reviewed
Institute(s)
Helmholtz AI - DLR (HAI - DLR)
Scopus ID
85121124913
Erfassungsdatum
2022-02-02