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Paper Abstract and Keywords
Presentation 2023-12-14 16:50
Dueling Networks Architecture in the Deep Reinforcement Learning for the Automated ICT System Design
Tianchen Zhou (Sophia Univ.), Yutaka Yakuwa (NEC), Natsuki Okamura, Hiroyuki Hochigai (Sophia Univ.), Takayuki Kuroda (NEC), Ikuko E. Yairi (Sophia Univ.) NS2023-135
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents a reinforcement learning based approach for the design of ICT systems. The automated ICT system design technology faces a fundamental challenge characterized by prolonged learning times, primarily attributable to the tendency to overestimate particular configurations due to the scarcity of rewards, despite the vast exploration space encompassing numerous possible combinations of ICT system components. The proposed method aims to improve the graph neural network structure for Q-value estimation by decomposing the network into two sub-streams to separately estimate global-state value and the state-dependent action advantage instead. By doing that, the dueling architecture can learn which states are whether valuable or not independently based on the global-state value, without having to learn the effect of each action for each state, giving more accurate approximation for Q-value. With better state value approximation, the network can achieve higher learning efficiency significantly but without imposing any change to the underlying reinforcement learning algorithm.
Keyword (in Japanese) (See Japanese page) 
(in English) System Design / Design Automation / Machine Learning / Reinforcement Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 307, NS2023-135, pp. 54-59, Dec. 2023.
Paper # NS2023-135 
Date of Issue 2023-12-07 (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 NS2023-135

Conference Information
Committee NS RCS  
Conference Date 2023-12-14 - 2023-12-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology Tobata campus, and Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Multi-hop/Relay/Cooperation, Disaster-resistant wireless network, Sensor/Mesh network, Ad-hoc network, D2D/M2M, Wireless network coding, Handover/AP switching/Connected cell control/Load balancing among base stations/Mobile network dynamic reconfiguration, QoS/QoE assurance, Wireless VoIP, IoT, Edge computing, etc. 
Paper Information
Registration To NS 
Conference Code 2023-12-NS-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dueling Networks Architecture in the Deep Reinforcement Learning for the Automated ICT System Design 
Sub Title (in English)  
Keyword(1) System Design  
Keyword(2) Design Automation  
Keyword(3) Machine Learning  
Keyword(4) Reinforcement Learning  
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1st Author's Name Tianchen Zhou  
1st Author's Affiliation Sophia University (Sophia Univ.)
2nd Author's Name Yutaka Yakuwa  
2nd Author's Affiliation NEC Corporation (NEC)
3rd Author's Name Natsuki Okamura  
3rd Author's Affiliation Sophia University (Sophia Univ.)
4th Author's Name Hiroyuki Hochigai  
4th Author's Affiliation Sophia University (Sophia Univ.)
5th Author's Name Takayuki Kuroda  
5th Author's Affiliation NEC Corporation (NEC)
6th Author's Name Ikuko E. Yairi  
6th Author's Affiliation Sophia University (Sophia Univ.)
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Speaker Author-1 
Date Time 2023-12-14 16:50:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2023-135 
Volume (vol) vol.123 
Number (no) no.307 
Page pp.54-59 
#Pages 6 
Date of Issue 2023-12-07 (NS) 

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