| Presentation | 2019-03-14 Improvement of Near-miss Courses by Reinforcement Learning to Search Ships' Courses Takahiro Tomihara, Takeshi Kamio, Takahiro Tanaka, Kunihiko Mitsubori, Hisato Fujisaka, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Deciding efficient and safe courses of ships before actual navigation is very important. We have developed multi-agent reinforcement learning system (MARLS) to search ships’ courses as a useful tool to discuss the appropriateness of courses and the interaction between maneuvering actions. In this research, we propose a new MARLS to improve near-miss courses as an expansion of our conventional MARLS which can improve reference courses. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Multi-ship course problem / Reinforcement learning / Multi-agent system / Reference courses / Near-miss courses |
| Paper # | NLP2018-127 |
| Date of Issue | 2019-03-07 (NLP) |
| Conference Information | |
| Committee | NLP / MSS |
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| Conference Date | 2019/3/14(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunkyo Camp., Univ. of Fukui |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | SICE-DES, IEICE-MSS, IEICE-NLP, Work In Progress, and etc. |
| Chair | Norikazu Takahashi(Okayama Univ.) / Morikazu Nakamura(Univ. of Ryukyus) |
| Vice Chair | Hiroaki Kurokawa(Tokyo Univ. of Tech.) / Shigemasa Takai(Osaka Univ.) |
| Secretary | Hiroaki Kurokawa(Hiroshima Inst. of Tech.) / Shigemasa Takai(Nippon Inst. of Tech.) |
| Assistant | Masayuki Kimura(Kyoto Univ.) / Yutaka Shimada(Saitama Univ.) / Hideki Kinjo(Okinawa Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Nonlinear Problems / Technical Committee on Mathematical Systems Science and its applications |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of Near-miss Courses by Reinforcement Learning to Search Ships' Courses |
| Sub Title (in English) | |
| Keyword(1) | Multi-ship course problem |
| Keyword(2) | Reinforcement learning |
| Keyword(3) | Multi-agent system |
| Keyword(4) | Reference courses |
| Keyword(5) | Near-miss courses |
| 1st Author's Name | Takahiro Tomihara |
| 1st Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| 2nd Author's Name | Takeshi Kamio |
| 2nd Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| 3rd Author's Name | Takahiro Tanaka |
| 3rd Author's Affiliation | Japan Coast Guard Academy(Japan Coast Guard Academy) |
| 4th Author's Name | Kunihiko Mitsubori |
| 4th Author's Affiliation | Takusyoku University(Takusyoku Univ.) |
| 5th Author's Name | Hisato Fujisaka |
| 5th Author's Affiliation | Hiroshima City University(Hiroshima City Univ.) |
| Date | 2019-03-14 |
| Paper # | NLP2018-127 |
| Volume (vol) | vol.118 |
| Number (no) | NLP-498 |
| Page | pp.pp.17-22(NLP), |
| #Pages | 6 |
| Date of Issue | 2019-03-07 (NLP) |