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Paper Abstract and Keywords
Presentation 2010-03-10 17:05
Autonomous Composition of State Space Based on Action History Table in Reinforcement Learning
Michio Kimura, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2009-185
Abstract (in Japanese) (See Japanese page) 
(in English) In the reinforcement learning, the discrete state space is generally constructed for red environments. and learning agents learn the policy in to each state. A high-dimensional and detailed discretization is often needed in the state input in the real environments. In order to learn practical tasks, it is necessary to reduce a huge computational complexity because of an increase in the number of states. Then, this study aims to reduce the computational complexity in large-scale environments. And, more efficient learning method based on an autonomous composition of state space is presented. Concretely, a method for designing state sets that considers state transitions is proposed.
Keyword (in Japanese) (See Japanese page) 
(in English) Reinforcement learning / Autonomous composition of state space / Speeding up / / / / /  
Reference Info. IEICE Tech. Rep., vol. 109, no. 458, NLP2009-185, pp. 149-154, March 2010.
Paper # NLP2009-185 
Date of Issue 2010-03-02 (NLP) 
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 NLP  
Conference Date 2010-03-09 - 2010-03-10 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NLP 
Conference Code 2010-03-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Autonomous Composition of State Space Based on Action History Table in Reinforcement Learning 
Sub Title (in English)  
Keyword(1) Reinforcement learning  
Keyword(2) Autonomous composition of state space  
Keyword(3) Speeding up  
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1st Author's Name Michio Kimura  
1st Author's Affiliation Tokyo City University (Tokyo City Univ.)
2nd Author's Name Hidehiro Nakano  
2nd Author's Affiliation Tokyo City University (Tokyo City Univ.)
3rd Author's Name Arata Miyauchi  
3rd Author's Affiliation Tokyo City University (Tokyo City Univ.)
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Speaker Author-1 
Date Time 2010-03-10 17:05:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2009-185 
Volume (vol) vol.109 
Number (no) no.458 
Page pp.149-154 
#Pages 6 
Date of Issue 2010-03-02 (NLP) 

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