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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NLP2009-185 |
Conference Information |
Committee |
NLP |
Conference Date |
2010-03-09 - 2010-03-10 |
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(See Japanese page) |
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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 |
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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 |
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Tokyo City University (Tokyo City Univ.) |
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Arata Miyauchi |
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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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