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  Learning and Control Strategies for Cyber-physical Systems: From Wireless Control over Deep Reinforcement Learning to Causal Identification

Baumann, D. (2020). Learning and Control Strategies for Cyber-physical Systems: From Wireless Control over Deep Reinforcement Learning to Causal Identification. PhD Thesis, KTH Royal Institute of Technology, Stockholm.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-5143-1 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-5144-0
Genre: Thesis

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 Creators:
Baumann, Dominik1, 2, Author           
Affiliations:
1Max Planck Research Group Intelligent Control Systems, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_2579691              
2KTH Royal Institute of Technology, Stockholm, Sweden, ou_persistent22              

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Free keywords: Forschungsgruppe Trimpe
 Abstract: -

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Language(s): eng - English
 Dates: 2020-12-09
 Publication Status: Accepted / In Press
 Pages: 263
 Publishing info: Stockholm : KTH Royal Institute of Technology
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: baumann2020learning
URI: http://kth.diva-portal.org/smash/record.jsf?pid=diva2%3A1500552&dswid=4823
URN: urn:nbn:se:kth:diva-285899
ISBN: 978-91-7873-696-6
 Degree: PhD

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