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Paper Abstract and Keywords
Presentation 2022-04-15 10:45
[Encouragement Talk] An Actor-Critic based Reinforcement Learning Algorithm for Combinatorial Optimization and Mobile Power Trucks Routing Problem
Zhao Wang (NTT), Yuhei Senuma (Waseda Univ.), Yuusuke Nakano (NTT), Jun Ohya (Waseda Univ.), Ken Nishimatsu (NTT) NS2022-1
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose an Actor-Critic based reinforcement learning (RL) algorithm for solving the traditional combinatorial optimization problem and a mobile power trucks routing problem (MPTRP), which is a new problem setting for automatically generating charging routes of mobile power trucks for telecommunication exchange buildings right after a disaster. Experimental results demonstrate that our proposed method not only outperforms previous RL methods in the travelling salesman problem (TSP) and large-scale TSP, which we believe are quite challenging tasks, but also solves MPTRP with a good generalized performance considering real-world circumstances such as traffic conditions and charging time cost.
Keyword (in Japanese) (See Japanese page) 
(in English) Reinforcement Learning / Actor-Critic / Combinatorial Optimization / TSP / Disaster Response of Telecommunication Exchange Building / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 5, NS2022-1, pp. 1-6, April 2022.
Paper # NS2022-1 
Date of Issue 2022-04-08 (NS) 
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 NS2022-1

Conference Information
Committee NS  
Conference Date 2022-04-15 - 2022-04-15 
Place (in Japanese) (See Japanese page) 
Place (in English) kikai shinkou kaikan + online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General 
Paper Information
Registration To NS 
Conference Code 2022-04-NS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Actor-Critic based Reinforcement Learning Algorithm for Combinatorial Optimization and Mobile Power Trucks Routing Problem 
Sub Title (in English)  
Keyword(1) Reinforcement Learning  
Keyword(2) Actor-Critic  
Keyword(3) Combinatorial Optimization  
Keyword(4) TSP  
Keyword(5) Disaster Response of Telecommunication Exchange Building  
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1st Author's Name Zhao Wang  
1st Author's Affiliation NTT LAB (NTT)
2nd Author's Name Yuhei Senuma  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Yuusuke Nakano  
3rd Author's Affiliation NTT LAB (NTT)
4th Author's Name Jun Ohya  
4th Author's Affiliation Waseda University (Waseda Univ.)
5th Author's Name Ken Nishimatsu  
5th Author's Affiliation NTT LAB (NTT)
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Speaker Author-1 
Date Time 2022-04-15 10:45:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2022-1 
Volume (vol) vol.122 
Number (no) no.5 
Page pp.1-6 
#Pages 6 
Date of Issue 2022-04-08 (NS) 

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