Record link: 
http://hdl.handle.net/20.500.12708/148133
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Title: 
Reciprocal Learning in Human-Machine Collaboration: A Multi-Agent System Framework in Industry 5.0
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Citation: 
Nixdorf, S., Ansari, F., & Schlund, S. (2022). Reciprocal Learning in Human-Machine Collaboration: A Multi-Agent System Framework in Industry 5.0. In P. Plapper (Ed.), Digitization of the work environment for sustainable production (pp. 207–225). GITO-Verlag. https://doi.org/10.30844/WGAB_2022_11
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Publisher DOI: 
10.30844/WGAB_2022_11
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
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Authors: 
Nixdorf, Steffen 
Ansari, Fazel 
Schlund, Sebastian 
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Organisational Unit: 
E330-02 - Forschungsbereich Betriebstechnik, Systemplanung und Facility Management 
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Published in: 
Digitization of the work environment for sustainable production 
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ISBN: 
978-3-95545-407-4
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Volume: 
2022
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DOI of the book: 
10.30844/wgab_2022
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Date (published): 
2022
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Event name: 
WGAB research seminar 2022 
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Event date: 
9-Sep-2022 - 10-Sep-2022
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Event place: 
Luxembourg, Luxembourg
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Number of Pages: 
19
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Publisher: 
GITO-Verlag, Berlin
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Keywords: 
Industry 5.0; Reciprocal Learning; Human-Machine Symbiosis
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Link (external): 
https://library.gito.de/en/category/wgab/
https://library.gito.de/wp-content/uploads/2022/08/WGAB2022_11_Nixdorf_Wien.pdf
https://library.gito.de/en/2022/08/wgab22-11_nixdorf/
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Research Areas: 
Digital Transformation in Manufacturing: 100%
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Science Branch: 
1020 - Informatik: 20%
5020 - Wirtschaftswissenschaften: 50%
2119 - Sonstige Technische Wissenschaften: 30%
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Appears in Collections:
Conference Paper

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