| Author | Search for: Brown, Jeffrey S.1; Search for: Veitch, Brian1 |
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| Affiliation | - National Research Council of Canada. Ocean, Coastal and River Engineering
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| Format | Text, Article |
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| Conference | SNAME Maritime Convention 2020, SMC 2020, September 29 - October 2, 2020, Virtual, Online |
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| Subject | ice management; marine operations; marine simulators; reinforcement learning |
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| Abstract | 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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| Publication date | 2020-09-29 |
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| Publisher | Society of Naval Architects and Marine Engineers |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 5db09f48-d072-403a-b37e-7aa9959a8fda |
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| Record created | 2022-07-21 |
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| Record modified | 2022-07-21 |
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