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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 277  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
RCS, SIP, IT 2022-01-20
10:55
Online Online Rate-compatible LDPC Code in Dynamic Environment based on Reinforcement Learning
Li Zizhen, Shan Lu, Hiroshi Kamabe (Gifu Univ.) IT2021-35 SIP2021-43 RCS2021-203
To balance the time delay caused by switching code rates and the system performance, we proposed a code rate switching a... [more] IT2021-35 SIP2021-43 RCS2021-203
pp.40-44
SeMI 2022-01-21
09:40
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] Study of ACK-Less Rate Adaptation for IEEE 802.11bc Using Deep Reinforcement Learning
Takamochi Kanda (Kyoto Univ.), Yusuke Koda (Univ. of Oulu), Yuto Kihira, Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.) SeMI2021-74
This paper introduces an ACK-less rate adaptation to locational variation of recipient stations (STAs) for broadcast wir... [more] SeMI2021-74
pp.86-88
SS, MSS 2022-01-11
14:05
Nagasaki Nagasakiken-Kensetsu-Sogo-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
Design of Self-Triggered Reduced-Order Controllers of Probabilistic Boolean Networks Using Reinforcement Learning
Michiaki Takizawa, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) MSS2021-37 SS2021-24
We consider the stabilization of Probabilistic Boolean Networks using reinforcement learning. Using reinforcement learni... [more] MSS2021-37 SS2021-24
pp.35-39
NLP 2021-12-17
11:15
Oita J:COM Horuto Hall OITA Investigation on Distance Between Probability Distributions in Trust Region Policy Optimization
Kenta Sugaya, Hidehiro Nakano (Tokyo City Univ.) NLP2021-46
In this paper, we propose a method to change Kullback-Leibler Divergence to Jensen-Shannon Divergence that used in Trust... [more] NLP2021-46
pp.18-21
RCS, NS
(Joint)
2021-12-17
14:30
Nara Nara-ken Bunka Kaikan and Online
(Primary: On-site, Secondary: Online)
[Invited Lecture] Energy-Efficient DQN-based User Association for Sub6GHz/mmWave Networks
Megumi Kaneko, Thi Ha Ly Dinh (NII), Keisuke Wakao, Kenichi Kawamura, Takatsune Moriyama, Yasushi Takatori (NTT) NS2021-109 RCS2021-192
This work investigates the design of an energy-efficient Deep Q-Network (DQN) implemented at the user device, whose purp... [more] NS2021-109 RCS2021-192
p.65(NS), p.88(RCS)
IN, IA
(Joint)
2021-12-17
18:10
Hiroshima Higashi-Senda campus, Hiroshima Univ.
(Primary: On-site, Secondary: Online)
[Short Paper] Study on Improving the Characteristics of Random Walk on Graph using Q-learning
Tomoyuki Miyashita, Taisei Suzuki, Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2021-51
In recent years, modeling mobile agent on unknown graphs, such as random walks on graphs and understanding its mathemati... [more] IA2021-51
pp.100-103
MSS, CAS, IPSJ-AL [detail] 2021-11-18
09:00
Online Online Design and Implementation of a Distributed Building Control Simulator for Federated Learning
Shugo Fujimura, Koki Fujita, Yuwei Sun, Hiroshi Esaki, Hideya Ochiai (UTokyo) CAS2021-37 MSS2021-17
Toward a sustainable society in the 2050s, zero-energy buildings have been proposed, which consume virtually no energy b... [more] CAS2021-37 MSS2021-17
pp.1-6
MSS, CAS, IPSJ-AL [detail] 2021-11-18
09:25
Online Online A Proposal of the Control Method for Multiple Buildings with AI Techiques
Koki Fujita, Shugo Fujimura, Yuwei Sun, Hiroshi Esaki, Hideya Ochiai (UTokyo) CAS2021-38 MSS2021-18
In recent years, the use of AI techniques for controlling building facilities has begun to be proposed. In the future, b... [more] CAS2021-38 MSS2021-18
pp.7-12
CCS 2021-11-19
11:10
Osaka Osaka Univ.
(Primary: On-site, Secondary: Online)
Toward Human Cognition-inspired High-Level Decision Making For Hierarchical Reinforcement Learning Agents
Rousslan Fernand Julien Dossa (Kobe Univ.), Takashi Matsubara (Osaka Univ.) CCS2021-28
Hierarchical reinforcement learning (HRL) methods aim to leverage the concept of temporal abstraction to efficiently sol... [more] CCS2021-28
pp.61-66
RISING
(3rd)
2021-11-17
09:00
Tokyo
(Primary: On-site, Secondary: Online)
An Efficient Channel Assignment based on Deep Reinforcement Learning in Heterogeneous Wireless Network with Unlicensed Bands
Bayarmaa Ragchaa, Kazuhiko Kinoshita (Tokushima Univ.)
In recent years, the amount of data traffic is growing rapidly and spectrum resources are scarcity in wireless networks.... [more]
MBE, NC
(Joint)
2021-10-28
16:20
Online Online Study on rounding error and Learning performance of reinforcement learning model for FPGA implementation
Daisuke Oguchi, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2021-24
In recent years, the hardware implementation of reinforcement learning (RL) has attracted attention due to its wide rang... [more] NC2021-24
pp.34-39
MIKA
(3rd)
2021-10-28
10:30
Okinawa
(Primary: On-site, Secondary: Online)
[Poster Presentation] Adaptive Server Selection Method Using Deep Reinforcement Learning for MPEG-DASH
Jun Yasui, Tomotaka Kimura, Jun Cheng (Doshisha Univ.)
In recent years, with the increase in the number of users of live streaming services, communication bandwidth has become... [more]
MIKA
(3rd)
2021-10-29
10:30
Okinawa
(Primary: On-site, Secondary: Online)
[Poster Presentation] Implementation and experimental evaluation of MAB-based channel selection algorithm for LoRa devices
Minoru Fujisawa, Aohan Li, Ikumi Urabe, Ryoma Kitagawa, Yusuke Ito (TUS), Song-Ju Kim (SOBIN Institute LLC), Hiroyuki Yasuda (UTokyo), Mikio Hasegawa (TUS)
In recent years, the number of IoT devices has been increasing rapidly, and traffic is also expected to increase. In an ... [more]
CQ, MIKA
(Joint)
2021-09-09
16:00
Online Online Network Slicing Resource Allocation Algorithm Based on Deep Q-Learning
Honglin Zhou, Hitoshi Aida (UTokyo) CQ2021-48
As a key technology of 5G communication system, network slicing can guarantee the QoS of different service requirements ... [more] CQ2021-48
pp.48-52
CQ, MIKA
(Joint)
2021-09-10
10:10
Online Online Deep Reinforcement Learning Based Mode Selection for Coexistence of D2D-Unlicensed and Wi-Fi
Wang Ganggui, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-52
The use of unlicensed bands on Device to Device (D2D) communication provides support for shortage of spectrum resources.... [more] CQ2021-52
pp.71-76
IN, NS, CS, NV
(Joint)
2021-09-09
14:30
Online Online [Invited Lecture] A Proposal and Implementation of Adaptive Distributed Compressed Sensing with Cooperative Optimization among Edge Devices
Masatoshi Sekine, Kengo Okano, Satoshi Ikada (OKI) NS2021-64
In recent years, monitoring systems that utilize IoT have become important in monitoring social infrastructure and facto... [more] NS2021-64
pp.42-47
SWIM, SC 2021-08-27
10:25
Online Online Combining Multiagent Reinforcement Learning and Discrete Event Modeling for Pathfinding on a Non-Grid Graph
Shiyao Ding (Kyoto Univ.), Hideki Aoyama (Panasonic), Donghui Lin (Kyoto Univ.) SWIM2021-15 SC2021-13
In this report, we study a new multiagent path finding (MAPF) problem where multiple agents move on a non-grid graph wit... [more] SWIM2021-15 SC2021-13
pp.13-17
OPE, MW, IEE-EMT, MWP, EST, EMT, THz [detail] 2021-07-15
13:00
Online Online Acquisition of Automatic Design Techniques for Microstrip BPF with Transmission Zeros through Deep Reinforcement Learning
Kohei Takano, Masataka Ohira, Zhewang Ma (Saitama Univ.) EMT2021-11 MW2021-16 OPE2021-5 EST2021-12 MWP2021-13
This paper investigates the acquisition of an automatic design technique for a microstrip bandpass filter (BPF) having t... [more] EMT2021-11 MW2021-16 OPE2021-5 EST2021-12 MWP2021-13
pp.22-27
SIP, CAS, VLD, MSS 2021-07-06
11:15
Online Online Pinning Stabilization of Probabilistic Boolean Networks Using Reinforcement Learning
Michiaki Takizawa, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) CAS2021-12 VLD2021-12 SIP2021-22 MSS2021-12
We consider the pinning stabilization of probabilistic Boolean networks using reinforcement learning. Using reinforcemen... [more] CAS2021-12 VLD2021-12 SIP2021-22 MSS2021-12
pp.60-63
SR 2021-05-21
10:50
Online Online Performance Evaluation of Distributed Channel Selection Algorithm Based on Reinforcement Learning for Massive Mobile IoT Systems
Daisuke Yamamoto, Honami Furukawa, Yusuke Ito, Aohan Li (TUS), Song-Ju Kim (Keio Univ.), Mikio Hasegawa (TUS) SR2021-11
In a Massive IoT environment, degradation of communication quality due to network congestion is a serious problem. In pr... [more] SR2021-11
pp.73-78
 Results 1 - 20 of 277  /  [Next]  
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