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Paper Abstract and Keywords
Presentation 2008-01-29 13:55
A Study on Applying Reinforcement Learning to a Safety Critical System
Shinichi Fujiwara, Toshiyuki Miyamoto, Sadatoshi Kumagai (Osaka Univ.) CST2007-53
Abstract (in Japanese) (See Japanese page) 
(in English) Reinforcement Learning have been attracting many researchers attention as a framework of autonomous cooperative behavior acquisition. In this framework, actor adapts to an environment with the help of a reward obtained as a result of the trial-and-error or application of self knowledge.
Now, we discuss a possibility to apply a multi-agent reinforcement learning to already proposed damage control mechanism of Safety Critical System(SCS). In the SCS, we suppose the total system is divided into some sections and performance is secured by controlling damages under a certain level. Then we employ a reinforcement learning method for a decision-making of damage control mechanism. SCS is different from existing other testbed of multi-agent reinforcement learning because it is similar to the concept of the Quality of Service in that we control damages differently according to each required damage level. According to a simulation the Q-learning is employed as a reinforcement learning method, we regarded the reinforcement learning is possible to apply to the SCS.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-agent System / Reinforcement Learning / Q-learning / Safety Critical System / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, Jan. 2008.
Paper #  
Date of Issue 2008-01-22 (CST) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
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  
Conference Date 2008-01-28 - 2008-01-29 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Tokushima 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Concurrent Systems, CST Solution Competition 2007 
Paper Information
Registration To MSS 
Conference Code 2008-01-CST 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Applying Reinforcement Learning to a Safety Critical System 
Sub Title (in English)  
Keyword(1) Multi-agent System  
Keyword(2) Reinforcement Learning  
Keyword(3) Q-learning  
Keyword(4) Safety Critical System  
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1st Author's Name Shinichi Fujiwara  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Toshiyuki Miyamoto  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Sadatoshi Kumagai  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker
Date Time 2008-01-29 13:55:00 
Presentation Time 25 
Registration for MSS 
Paper # IEICE-CST2007-53 
Volume (vol) IEICE-107 
Number (no) no.472 
Page pp.41-46 
#Pages IEICE-6 
Date of Issue IEICE-CST-2008-01-22 


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