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|a 1000156002
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|a Lohse, Oliver
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| 245 |
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|a Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung
|h Elektronische Ressource
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| 260 |
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|b KIT Scientific Publishing
|c 2023
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| 300 |
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|a 1 electronic resource (208 p.)
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| 653 |
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|a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials
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| 653 |
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|a Produktionssteuerung; Reinforcement Learning; Künstliche Intelligenz; Terminierung; Production control; artificial intelligence; scheduling
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| 041 |
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7 |
|a deu
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 490 |
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|a Reihe Informationsmanagement im Engineering Karlsruhe
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/
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| 024 |
8 |
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|a 10.5445/KSP/1000156002
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| 856 |
4 |
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|u https://directory.doabooks.org/handle/20.500.12854/99534
|z DOAB: description of the publication
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| 856 |
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|u https://library.oapen.org/bitstream/20.500.12657/62536/1/entwicklung-einer-methode-zum-einsatz-von-reinforcement-learning-fur-die-dynamische-fertigungsdurchlaufsteuerung.pdf
|7 0
|x Verlag
|3 Volltext
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| 082 |
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|a 630
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| 082 |
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|a 700
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|a 600
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|a 620
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|a This work aims to develop a method that can reschedule the matrix production in the case of a disruption. For this purpose, different artificial intelligence methods are combined in a novel way. The developed method is validated on a theoretical and a real scheduling case.
|