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Paper Abstract and Keywords
Presentation 2007-06-15 09:25
Reinforcement Learning for Cooperative Actions in a Partially Observable Multi-Agent System
Yuki Taniguchi, Takeshi Mori, Shin Ishii (NAIST) NC2007-15
Abstract (in Japanese) (See Japanese page) 
(in English) In this article, we apply a policy gradient-based reinforcement learning to allowing multiple agents to perform cooperative actions in a partially observable environment. We introduce an auxiliary state variable, an internal state, whose stochastic process is Markov, for extracting important features of multi-agent's dynamics. Computer simulations show that every agent can identify an appropriate internal state model and acquire a good policy; this approach is shown to be more effective than a traditional memory-based method.
Keyword (in Japanese) (See Japanese page) 
(in English) Partially observable environments / Internal state / Policy gradient method / Multi-agent system / Cooperative action / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 92, NC2007-15, pp. 41-45, June 2007.
Paper # NC2007-15 
Date of Issue 2007-06-07 (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 NC2007-15

Conference Information
Committee NC  
Conference Date 2007-06-14 - 2007-06-15 
Place (in Japanese) (See Japanese page) 
Place (in English) OIST Seaside House 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2007-06-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reinforcement Learning for Cooperative Actions in a Partially Observable Multi-Agent System 
Sub Title (in English)  
Keyword(1) Partially observable environments  
Keyword(2) Internal state  
Keyword(3) Policy gradient method  
Keyword(4) Multi-agent system  
Keyword(5) Cooperative action  
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1st Author's Name Yuki Taniguchi  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Takeshi Mori  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Shin Ishii  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2007-06-15 09:25:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2007-15 
Volume (vol) vol.107 
Number (no) no.92 
Page pp.41-45 
#Pages 5 
Date of Issue 2007-06-07 (NC) 

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