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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 21  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP 2021-12-17
10:25
Oita J:COM Horuto Hall OITA Reinforcement learning to find ships' courses that ignores navigation rules based on safety
Mikito Tanaka, Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takushoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) NLP2021-44
 [more] NLP2021-44
pp.7-12
MSS, NLP
(Joint)
2020-03-10
16:45
Aichi  
(Cancelled but technical report was issued)
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
We have developed multi-agent reinforcement learning system (MARLS) to search ships’ courses. Since the rudder angle is ... [more] NLP2019-131
pp.103-108
NLP, MSS
(Joint)
2019-03-14
14:20
Fukui Bunkyo Camp., Univ. of Fukui Improvement of Near-miss Courses by Reinforcement Learning to Search Ships' Courses
Takahiro Tomihara, Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takusyoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) NLP2018-127
Deciding efficient and safe courses of ships before actual navigation is very important. We have developed multi-agent r... [more] NLP2018-127
pp.17-22
NLP, CAS 2017-10-06
13:25
Niigata Machinaka Campus Nagaoka Influence of Updating Reference Courses on Reinforcement Learning to Search Ships' Courses
Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takushoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) CAS2017-38 NLP2017-63
Deciding efficient and safe courses of ships before actual navigation is very important. We have developed multi-agent r... [more] CAS2017-38 NLP2017-63
pp.75-80
NLP 2017-03-14
10:50
Aomori Nebuta Museum Warasse Influence of Reference Courses on Reinforcement Learning to Search Ships' Courses
Takeshi Kamio, Shunsuke Yasui (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takushoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) NLP2016-108
Deciding efficient and safe courses of ships before actual navigation is very important. We have developed multi-agent r... [more] NLP2016-108
pp.13-18
NLP, CCS 2015-06-12
09:25
Tokyo Waseda Univerisity Toward Implementation of the labyrinth exploration by the intelligent mobile robots
Jun Ishihara, Kunihiko Mitsubori (Takushoku Univ.) NLP2015-55 CCS2015-17
A purpose of this study is to explore the labyrinth by the real mobile robots. Each robot has the sensors to collect the... [more] NLP2015-55 CCS2015-17
pp.97-102
NLP 2013-07-08
13:50
Okinawa Miyako Island Marine Terminal An asynchronous multi-agent system selecting the destination based on the queue's length
Yuta Kazama, Kunihiko Mitsubori (Takushoku Univ.) NLP2013-32
This paper considers a pedestrian stream model with the interaction between the pedestrians and the queues based on the ... [more] NLP2013-32
pp.31-36
NLP 2013-03-14
09:30
Chiba Nishi-Chiba campus, Chiba Univ. Improvement of Limited Action Selection in Reinforcement Learning Based Search Method for Ships' Courses
Tomohiro Tanigawa, Takeshi Kamio (Hiroshima City Univ.), Kunihiko Mitsubori (Takushoku Univ.), Takahiro Tanaka (Japan Coast Guard Acad.), Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2012-144
Ship transport is important. Multi ship course problem has been treared in the engineering related to ships. But the opt... [more] NLP2012-144
pp.1-5
NLP 2012-07-05
14:20
Kagoshima Kagoshima Sangyou Hall Novel Participant Stream Model in Event Site Based on Multi-Agent System
Ikuya Maezawa, Kunihiko Mitsubori (Takushoku Univ.) NLP2012-42
This paper proposes a model of the participant stream in event site, based on Multi-Agent System. The event site has the... [more] NLP2012-42
pp.23-28
NLP 2012-07-05
14:45
Kagoshima Kagoshima Sangyou Hall Digital Circuit Design of A Pedestrian Flow Model Based on Multi-Agent System
Takashi Toyofuku, Kunihiko Mitsubori (Takushoku Univ.) NLP2012-43
Recently, many researchers try to construct the models of the pedestrian flow by using the cellular automata. Such a mod... [more] NLP2012-43
pp.29-34
NLP 2012-01-24
10:10
Fukushima Aizu-keiko-do Hall Analysis of chaotic spiking oscillators that fire depending on state and time
Kazuki Yotsuji, Satoshi Imai (HU), Kunihiko Mitsubori (Takushoku Univ.), Toshimichi Saito (HU) NLP2011-136
This paper studies chaotic spiking oscillators controlled by impulsive switching depending on both time and state.
If ... [more]
NLP2011-136
pp.69-73
NLP 2011-11-09
13:15
Okinawa Miyako Island Marine Terminal Basic dynamics of chaotic spiking oscillators with two thresholds
Shinya Tanaka, Toshimichi Saito (HU), Kunihiko Mitsubori (TU) NLP2011-98
This paper presents piecewise constant chaotic spiking oscillators with two firing thresholds.
In the case of single f... [more]
NLP2011-98
pp.37-42
NLP 2010-03-09
10:20
Tokyo   Finding Course of Ships by Multi-Agent Reinforcement Learning with A Priori Knowledge
Takeshi Kamio (Hiroshima City Univ.), Kunihiko Mitsubori (Takusyoku Univ.), Takahiro Tanaka (Japan Coast Gurad Academy), Chang-Jun Ahn, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2009-161
 [more] NLP2009-161
pp.21-26
NLP 2009-03-11
14:50
Kyoto   Reinforcement Learning to Find the Course of Multi-Ships
Shohei Sugeo, Takeshi Kamio (Hiroshima City Univ.), Kunihiko Mitsubori (Takushoku Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Chang-Jun Ahn, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2008-167
 [more] NLP2008-167
pp.93-98
NLP 2009-02-28
09:20
Kanagawa   Finding Route of A Four-wheels Car Based on Reinforcement Learning Algorithm
You Igarashi, Kunihiko Mitsubori (Takushoku Univ.) NLP2008-131
This article discusses finding the route of a four-wheel car based on the reinforcement learning algorithm. We consider ... [more] NLP2008-131
pp.1-6
NLP 2009-02-28
09:40
Kanagawa   Finding Route in a Multi-Agent Environment Based on Reinforcement Learning Algorithm
Kenji Masuda, Kunihiko Mitsubori (Takushoku Univ.) NLP2008-132
Recently, many researchers try to construct the models of the pedestrian flow by using the cellular automata. In the fie... [more] NLP2008-132
pp.7-11
NLP 2008-03-28
11:40
Hyogo   A Note on Expansion and Contraction of Categories in Fuzzy ARTMAP
Takeshi Kamio (Hiroshima City Univ.), Kunihiko Mitsubori (Takushoku Univ.), Chang-Jun Ahn, Hisato Fujisaka, Kazuhisa Haeiwa (Hiroshima City Univ.) NLP2007-171
Fuzzy ARTMAP (FAM) is a supervised learning system. FAM segments the input space with categories which are defined by hy... [more] NLP2007-171
pp.25-30
NLP 2005-06-23
13:15
Hiroshima Hiroshima City Univ. Finding the Course of a Ship and Reinforcement Learning Algorithm
Kunihiko Mitsubori (Japan Coast Guard Acad.), Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Acad.)
We consider the reinforcement learning algorithm to find the appropriate courses of two ships which avoid the collision ... [more] NLP2005-19
pp.19-24
NLP 2005-06-23
13:55
Hiroshima Hiroshima City Univ. n/a
n/a, Takeshi Kamio, Kunihiko Mitsubori, Hisato Fujisaka (n/a)
The trade-off between exploration and exploitation has often been discussed in studies on reinforcement learning (RL). T... [more] NLP2005-20
pp.25-30
NLP 2005-03-26
11:25
Tokyo Tokyo Univ n/a
Takeshi Kamio, Kenji Mori, Hisato Fujisaka (Hiroshima City Univ.), Kunihiko Mitsubori (Japan Coast Guard Academy)
It is important and difficult to find the appropriate course of a ship in a restricted sea-area with the strong tidal cu... [more] NLP2004-129
pp.25-30
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