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Paper Abstract and Keywords
Presentation 2020-03-10 16:45
Reinforcement Learning Based Multi-Ship Course Search Method with Tracking Control
Hiroki Kimura, Takahiro Tomihara, Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takushoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) NLP2019-131
Abstract (in Japanese) (See Japanese page) 
(in English) We have developed multi-agent reinforcement learning system (MARLS) to search ships’ courses. Since the rudder angle is defined as the action in our conventional MARLS, it tends to repeat useless course search. In this report, to overcome this problem, we propose a new MARLS which has the target course as defined the action. Also, each ship traces the target course by the tracking control. Finally, it has been confirmed by numerical experiments that our proposed MARLS has better learning efficiency than our conventional MARLS.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-ship course problem / Reinforcement learning / Multi-agent system / Target course / Tracking control / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 471, NLP2019-131, pp. 103-108, March 2020.
Paper # NLP2019-131 
Date of Issue 2020-03-02 (NLP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee MSS NLP  
Conference Date 2020-03-09 - 2020-03-10 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) SICE-DES, IEICE-MSS, IEICE-NLP 
Paper Information
Registration To NLP 
Conference Code 2020-03-MSS-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reinforcement Learning Based Multi-Ship Course Search Method with Tracking Control 
Sub Title (in English)  
Keyword(1) Multi-ship course problem  
Keyword(2) Reinforcement learning  
Keyword(3) Multi-agent system  
Keyword(4) Target course  
Keyword(5) Tracking control  
1st Author's Name Hiroki Kimura  
1st Author's Affiliation Hiroshima City University (Hiroshima City Univ.)
2nd Author's Name Takahiro Tomihara  
2nd Author's Affiliation Hiroshima City University (Hiroshima City Univ.)
3rd Author's Name Takeshi Kamio  
3rd Author's Affiliation Hiroshima City University (Hiroshima City Univ.)
4th Author's Name Takahiro Tanaka  
4th Author's Affiliation Japan Coast Guard Academy (Japan Coast Guard Academy)
5th Author's Name Kunihiko Mitsubori  
5th Author's Affiliation Takushoku University (Takushoku Univ.)
6th Author's Name Hisato Fujisaka  
6th Author's Affiliation Hiroshima City University (Hiroshima City Univ.)
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Speaker Author-1 
Date Time 2020-03-10 16:45:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2019-131 
Volume (vol) vol.119 
Number (no) no.471 
Page pp.103-108 
Date of Issue 2020-03-02 (NLP) 

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