Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung / / Oliver Lohse.

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.

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Place / Publishing House:Karlsruhe : : KIT Scientific Publishing,, 2023.
Year of Publication:2023
Language:German
Physical Description:1 online resource (208 pages)
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spelling Lohse, Oliver, author.
Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung / Oliver Lohse.
Karlsruhe : KIT Scientific Publishing, 2023.
1 online resource (208 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Description based on publisher supplied metadata and other sources.
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.
Reinforcement learning.
Reinforcement learning Congresses.
1000156002
language German
format eBook
author Lohse, Oliver,
spellingShingle Lohse, Oliver,
Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung /
author_facet Lohse, Oliver,
author_variant o l ol
author_role VerfasserIn
author_sort Lohse, Oliver,
title Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung /
title_full Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung / Oliver Lohse.
title_fullStr Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung / Oliver Lohse.
title_full_unstemmed Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung / Oliver Lohse.
title_auth Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung /
title_new Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung /
title_sort entwicklung einer methode zum einsatz von reinforcement learning für die dynamische fertigungsdurchlaufsteuerung /
publisher KIT Scientific Publishing,
publishDate 2023
physical 1 online resource (208 pages)
isbn 1000156002
callnumber-first Q - Science
callnumber-subject Q - General Science
callnumber-label Q325
callnumber-sort Q 3325.6 L647 42023
genre_facet Congresses.
illustrated Not Illustrated
dewey-hundreds 000 - Computer science, information & general works
dewey-tens 000 - Computer science, knowledge & systems
dewey-ones 006 - Special computer methods
dewey-full 006.31
dewey-sort 16.31
dewey-raw 006.31
dewey-search 006.31
work_keys_str_mv AT lohseoliver entwicklungeinermethodezumeinsatzvonreinforcementlearningfurdiedynamischefertigungsdurchlaufsteuerung
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is_hierarchy_title Entwicklung einer Methode zum Einsatz von Reinforcement Learning für die dynamische Fertigungsdurchlaufsteuerung /
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