Utilising Assured Multi-Agent Reinforcement Learning within safety-critical scenarios
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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In: Riley, J.; Calinescu, R.; Paterson, C.; Kudenko, D.; Banks, A.: Utilising Assured Multi-Agent Reinforcement Learning within safety-critical scenarios. In: Watrobski, J.; Salabun, W.; Toro, C.; Zanni-Merk, C.; Howlett, R.J.; Jain, L.C. (Eds.): Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES2021. Amsterdam [u.a.] : Elsevier, 2021 (Procedia Computer Science ; 192), S. 1061-1070. DOI: https://doi.org/10.1016/j.procs.2021.08.109
- Ereignis
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Veröffentlichung
- (wo)
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Hannover
- (wer)
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Gottfried Wilhelm Leibniz Universität Hannover
- (wann)
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2021
- Ereignis
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Veröffentlichung
- (wo)
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Hannover
- (wer)
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Technische Informationsbibliothek (TIB)
- (wann)
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2021
- Urheber
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Riley, Joshua
Calinescu, Radu
Paterson, Colin
Kudenko, Daniel
Banks, Alec
- DOI
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10.15488/15756
- URN
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urn:nbn:de:101:1-2023122101401961062816
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:44 MEZ
Datenpartner
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Beteiligte
- Riley, Joshua
- Calinescu, Radu
- Paterson, Colin
- Kudenko, Daniel
- Banks, Alec
- Gottfried Wilhelm Leibniz Universität Hannover
- Technische Informationsbibliothek (TIB)
Entstanden
- 2021
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