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

Baumann, Dominik

Local TagsRelease HistoryDetailsSummary

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.

Item is Released

show all hide all

Basic

show hide

Item Permalink: https://hdl.handle.net/21.11116/0000-0008-5143-1 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-CAE6-0

Genre: Thesis

Files

show Files

Locators

show

Creators

show

hide

Creators:
Baumann, Dominik^{1, 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, Schweden, ou_persistent22

Content

show

hide

Free keywords: Forschungsgruppe Trimpe

Abstract: -

Details

show

hide

Language(s): eng - English

Dates: Accepted: 2020-12-09

Publication Status: Accepted / In Press

Pages: XIV, 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

Event

show

Legal Case

show

Project information

show

Source

show