- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2045-2322
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Designing all-pay auctions using deep learning and multi-agent simulation ; volume:12 ; number:1 ; day:8 ; month:10 ; year:2022 ; pages:1-15 ; date:12.2022
Scientific reports ; 12, Heft 1 (8.10.2022), 1-15, 12.2022
- Creator
-
Gemp, Ian
Anthony, Thomas
Kramar, Janos
Eccles, Tom
Tacchetti, Andrea
Bachrach, Yoram
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-022-20234-3
- URN
-
urn:nbn:de:101:1-2022122621262532070888
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:32 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Gemp, Ian
- Anthony, Thomas
- Kramar, Janos
- Eccles, Tom
- Tacchetti, Andrea
- Bachrach, Yoram
- SpringerLink (Online service)
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