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Paper Abstract and Keywords
Presentation 2022-09-16 15:25

Kohei Matsumoto, Keisuke Yoneda, Toshiharu Sugawara (Waseda Univ.) AI2022-31
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a method for autonomously reducing energy consumption while satisfying quality requirements in the multi-agent cooperative patrolling problem (MACPP). Although it is important to execute tasks efficiently, executing tasks beyond the required quality may result in unnecessary energy consumption. In this study, we extend an existing method to reduce energy consumption by estimating that each agent satisfies a given quality requirement, and adjusting the estimation to reduce unnecessary actions. Evaluation experiments show that the proposed method is more effective than existing methods by introducing parameters that adaptively adjust energy-saving behaviors, thereby reducing energy consumption at the same time as satisfying the required quality.
Keyword (in Japanese) (See Japanese page) 
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Reference Info. IEICE Tech. Rep., vol. 122, no. 186, AI2022-31, pp. 73-78, Sept. 2022.
Paper # AI2022-31 
Date of Issue 2022-09-08 (AI) 
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)
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Conference Information
Committee AI  
Conference Date 2022-09-15 - 2022-09-16 
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Paper Information
Registration To AI 
Conference Code 2022-09-AI 
Language Japanese without English title) 
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1st Author's Name Kohei Matsumoto  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Keisuke Yoneda  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Toshiharu Sugawara  
3rd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2022-09-16 15:25:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2022-31 
Volume (vol) vol.122 
Number (no) no.186 
Page pp.73-78 
#Pages 6 
Date of Issue 2022-09-08 (AI) 

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