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  Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization

Bogdanovic, M., Khadiv, M., & Righetti, L. (2022). Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization. Frontiers in Robotics and AI, 9: 854212. doi:10.3389/frobt.2022.854212.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000F-E24C-D Version Permalink: https://hdl.handle.net/21.11116/0000-000F-E24D-C
Genre: Journal Article

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Locator:
https://doi.org/10.3389/frobt.2022.854212 (Publisher version)
Description:
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OA-Status:
Gold
Locator:
https://doi.org/10.48550/arXiv.2107.06629 (Preprint)
Description:
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OA-Status:
Green

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 Creators:
Bogdanovic, Miroslav1, Author           
Khadiv, Majid1, Author                 
Righetti, Ludovic1, 2, Author                 
Affiliations:
1Research Group Movement Generation and Control, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_2344693              
2External Organizations, ou_persistent22              

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Free keywords: Forschungsgruppe Righetti
 Abstract: -

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Language(s): eng - English
 Dates: 2022-08-312022-08-31
 Publication Status: Issued
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: BibTex Citekey: BogKhaRig22
DOI: 10.3389/frobt.2022.854212
arXiv: 2107.06629
 Degree: -

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Title: Frontiers in Robotics and AI
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Lausanne : Frontiers Media
Pages: - Volume / Issue: 9 Sequence Number: 854212 Start / End Page: - Identifier: ISSN: 2296-9144
CoNE: https://pure.mpg.de/cone/journals/resource/22969144