| Auteur | Rechercher : Brown, Jeffrey S.1; Rechercher : Veitch, Brian1 |
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| Affiliation | - Conseil national de recherches du Canada. Génie océanique, côtier et fluvial
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| Format | Texte, Article |
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| Conférence | SNAME Maritime Convention 2020, SMC 2020, September 29 - October 2, 2020, Virtual, Online |
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| Sujet | ice management; marine operations; marine simulators; reinforcement learning |
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| Résumé | Designing Maritime Operations for new or complex situations traditionally relies on extensive consultation and full-scale trials, both of which rely on input from domain experts. These methods are often expensive, time consuming and have potentially uncertain outcomes. A method to discover high performing maritime operations is proposed by applying reinforcement learning techniques using scenarios implemented in commercial marine simulation technology. The approach is demonstrated with a simple case study using a short transit operation. Details and limitations of the method are presented and discussed. |
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| Date de publication | 2020-09-29 |
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| Maison d’édition | Society of Naval Architects and Marine Engineers |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 5db09f48-d072-403a-b37e-7aa9959a8fda |
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| Enregistrement créé | 2022-07-21 |
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| Enregistrement modifié | 2022-07-21 |
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