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Paper Abstract and Keywords
Presentation 2021-03-03 14:50
Safe reinforcement learning in high-dimensional continuous spaces
Takumi Umemoto (NIT), Tohgoroh Matsui (Chubu Univ.), Atsuko Mutoh, Koich Moriyama, Inuzuka Nobuhiro (NIT) IBISML2020-50
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a method to extend the reinforcement learning method (CSEQ) based on success probability and profit in continuous state space to higher dimensions. Reinforcement learning is a machine learning method that learns better behavior based on trial and error, and there is a method called EQ based on success probability and profit as safe reinforcement learning focusing on learning danger avoidance behavior, and continuous observation Its effectiveness has been confirmed in the problem on the two-dimensional space of. We propose safe reinforcement learning that deals with high-dimensional continuous space using the mean values of latent variables modeled by VAE.
Keyword (in Japanese) (See Japanese page) 
(in English) reinforcement learning / safe reinforcement learning / deep learning / auto encoder / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 395, IBISML2020-50, pp. 55-62, March 2021.
Paper # IBISML2020-50 
Date of Issue 2021-02-23 (IBISML) 
ISSN 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 IBISML2020-50

Conference Information
Committee IBISML  
Conference Date 2021-03-02 - 2021-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Organized and general sessions on machine learning 
Paper Information
Registration To IBISML 
Conference Code 2021-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Safe reinforcement learning in high-dimensional continuous spaces 
Sub Title (in English)  
Keyword(1) reinforcement learning  
Keyword(2) safe reinforcement learning  
Keyword(3) deep learning  
Keyword(4) auto encoder  
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1st Author's Name Takumi Umemoto  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Tohgoroh Matsui  
2nd Author's Affiliation Chubu University (Chubu Univ.)
3rd Author's Name Atsuko Mutoh  
3rd Author's Affiliation Nagoya Institute of Technology (NIT)
4th Author's Name Koich Moriyama  
4th Author's Affiliation Nagoya Institute of Technology (NIT)
5th Author's Name Inuzuka Nobuhiro  
5th Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2021-03-03 14:50:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2020-50 
Volume (vol) vol.120 
Number (no) no.395 
Page pp.55-62 
#Pages 8 
Date of Issue 2021-02-23 (IBISML) 

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