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Paper Abstract and Keywords
Presentation 2011-03-07 17:15
Spatial representation in reinforcement learning
Tsubasa Asano, Satoshi Yamada (Okayama Univ. Sci.) NC2010-156
Abstract (in Japanese) (See Japanese page) 
(in English) It is important to use appropriate spatial representations in the reinforcement learning. Since Incremental Normalized Gaussian Network (INGnet) set a new unit at an appropriate position in the learning, it has the capability to make optimal representations. To apply INGnet to the control problems with more inputs, the modular reinforcement learning using INGnet (modular-RL(INGnet)) was proposed. RL(INGnet) learned the control where small changes in inputs should be distinguished. And modular-RL(INGnet) learned the control where the "AND" condition of two types of sensor information should be discriminated.
Keyword (in Japanese) (See Japanese page) 
(in English) Reinforcement Learning / Modular reinforcement learning / INGnet / / / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 461, NC2010-156, pp. 171-176, March 2011.
Paper # NC2010-156 
Date of Issue 2011-02-28 (NC) 
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)
Download PDF NC2010-156

Conference Information
Committee NC MBE  
Conference Date 2011-03-07 - 2011-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2011-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Spatial representation in reinforcement learning 
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Keyword(1) Reinforcement Learning  
Keyword(2) Modular reinforcement learning  
Keyword(3) INGnet  
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1st Author's Name Tsubasa Asano  
1st Author's Affiliation Okayama University of Science (Okayama Univ. Sci.)
2nd Author's Name Satoshi Yamada  
2nd Author's Affiliation Okayama University of Science (Okayama Univ. Sci.)
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Speaker
Date Time 2011-03-07 17:15:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2010-156 
Volume (vol) IEICE-110 
Number (no) no.461 
Page pp.171-176 
#Pages IEICE-6 
Date of Issue IEICE-NC-2011-02-28 


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