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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 300  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MIKA
(3rd)
2022-10-14
10:40
Niigata Niigata Citizens Plaza
(Primary: On-site, Secondary: Online)
[Poster Presentation] Reinforcement Learning-based Method for Reducing Power Consumption of BLE Advertisements
Minoru Fujisawa (Tokyo Univ. of Science), Hiroyuki Yasuda (The Univ. of Tokyo), Ryosuke Isogai, Yoshifumi Yoshida (SEIKO FUTURE CREATION INC.), Song-Ju Kim (SOBIN Inst.), Mikio Hasegawa (Tokyo Univ. of Science)
(To be available after the conference date) [more]
NC, MBE
(Joint)
2022-09-30
11:35
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
A dynamic state-space reinforcement learning model explaining functional differentiation of higher motor areas in the cerebral cortex
Naoki Tamura, Hajime Mushiake (Tohoku Univ), Kazuhiro Sakamoto (TMPU) NC2022-42
Complex and sequential behaviors based on various cues depend on the frontal higher motor areas of the cerebral cortex. ... [more] NC2022-42
pp.44-48
AI 2022-09-16
13:30
Shizuoka
(Primary: On-site, Secondary: Online)
Temporal Modeling of Players for Multi-agent Coordination in Non-Cooperative Game
Junjie Zhong, Toshiharu Sugawara (Waseda Univ.) AI2022-26
Multi-agent interaction structures that contain mixed cooperative-competitive relationships appear in many realistic sit... [more] AI2022-26
pp.48-53
IA, CQ, MIKA
(Joint)
2022-09-15
16:00
Hokkaido Hokkaido Citizens Actives Center
(Primary: On-site, Secondary: Online)
DRL-assisted Network Selection for Federated Learning
Ganggui Wang, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2022-34
Recently, with the development of wireless communication technologies such as 5G, more and more devices communicate thro... [more] CQ2022-34
pp.56-61
PN 2022-08-30
09:00
Hokkaido
(Primary: On-site, Secondary: Online)
Intelligent design and control of optical networks that adopts supplemental information on link adjacency and maximum link utilization
Kenji Cruzado, Ryuta Shiraki, Yojiro Mori (Nagoya Univ.), Takafumi Tanaka, Katsuaki Higashimori, Fumikazu Inuzuka, Takuya Ohara (NTT), Hiroshi Hasegawa (Nagoya Univ.) PN2022-14
We propose a reinforcement-learning-based network design and control algorithm that introduces stepwise reward variation... [more] PN2022-14
pp.31-35
SIP 2022-08-26
09:54
Okinawa Nobumoto Ohama Memorial Hall (Ishigaki Island)
(Primary: On-site, Secondary: Online)
A study on rate control using Deep Q-network in IEEE802.11
Tomoki Nakashima (Kyutech), Leonardo Lanante (Ofinno), Masayuki Kurosaki, Hiroshi Ochi (Kyutech) SIP2022-63
Transmission rate control in wireless LANs is one of the factors that affect communication quality. Although many transm... [more] SIP2022-63
pp.70-74
SAT, RCS
(Joint)
2022-08-26
09:50
Hokkaido
(Primary: On-site, Secondary: Online)
Joint UAV Positioning and User Pairing via Reinforcement Learning Based Selection in NOMA Systems
Ahmad Gendia, Osamu Muta (Kyushu Univ.), Sherief Hashima (RIKEN-AIP), Kohei Hatano (Kyushu Univ.) RCS2022-114
This paper proposes two reinforcement learning (RL)-based algorithms for millimeter wave (mmWave)-enabled unmanned aeria... [more] RCS2022-114
pp.96-101
SAT, RCS
(Joint)
2022-08-26
12:05
Hokkaido
(Primary: On-site, Secondary: Online)
Multi-Agent Deep Q-Learning based Inter-Cell Interference Coordination for Cellular Systems
Liu Yuchen, Chang Yuyuan, Fukawa Kazuhiko (Tokyo Tech) RCS2022-119
In small cell systems, inter-cell interference (ICI) can severely degrade the overall system capacity. To alleviate ICI,... [more] RCS2022-119
pp.126-131
IN, CCS
(Joint)
2022-08-04
14:20
Hokkaido Hokkaido University(Centennial Hall)
(Primary: On-site, Secondary: Online)
A Study of Low Power BLE Advertising Method Based on Reinforcement Learning
Hiroyuki Yasuda (The Univ. of Tokyo), Minoru Fujisawa (Tokyo Univ. of Science), Ryosuke Isogai, Yoshifumi Yoshida (SEIKO HOLDINGS Corp.), Song-Ju Kim (Tokyo Univ. of Science), Yozo Shoji (NICT), Kazuyuki Aihara (The Univ. of Tokyo), Mikio Hasegawa (Tokyo Univ. of Science) CCS2022-33
Bluetooth Low Energy (BLE) has been applied to various IoT services because of its versatility and energy efficiency. In... [more] CCS2022-33
pp.35-40
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-14
13:25
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Deep Reinforcement Learning-based IRS-aided Wireless Communication without Channel State Information
Hashida Hiroaki, Kawamoto Yuichi, Kato Nei (Tohoku Univ.), Iwabuchi Masashi, Murakami Tomoki (NTT) RCS2022-85
Intelligent reflecting surfaces (IRSs) have attracted attention as devices that enable radio propagation, which has been... [more] RCS2022-85
pp.84-89
AI 2022-07-04
10:20
Hokkaido
(Primary: On-site, Secondary: Online)
Designing Rewards in Deep Reinforcement Learning for Chick Feeding System
Masato Kijima, Katsuhide Fujita, Tsuyoshi Shimmura (TAT) AI2022-2
Livestock is raised cage-free, and there is an urgent need to develop an appropriate livestock management system.
The... [more]
AI2022-2
pp.7-12
CCS, NLP 2022-06-09
13:50
Osaka
(Primary: On-site, Secondary: Online)
Improvement of Learning Performance by Using a Symmetric Constraint Condition in PPO
Naoki Iwaya, Hidehiro Nakano (Tokyo City Univ.) NLP2022-3 CCS2022-3
Deep Reinforcement Learning (DRL) is an algorithm of learning the optimal action from the experiences. PPO KL Penalty, a... [more] NLP2022-3 CCS2022-3
pp.13-16
CCS, NLP 2022-06-09
15:45
Osaka
(Primary: On-site, Secondary: Online)
Reservoir computing with spiking neural networks and reward-modulated STDP
Takayuki Tsurumi, Gouhei Tanaka (UTokyo) NLP2022-7 CCS2022-7
In a previous study, it was verified that tasks requiring nonlinearity and working memory can be performed using reward-... [more] NLP2022-7 CCS2022-7
pp.31-35
NS 2022-04-15
10:45
Tokyo kikai shinkou kaikan + online
(Primary: On-site, Secondary: Online)
[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
In this paper, we propose an Actor-Critic based reinforcement learning (RL) algorithm for solving the traditional combin... [more] NS2022-1
pp.1-6
NS 2022-04-15
11:10
Tokyo kikai shinkou kaikan + online
(Primary: On-site, Secondary: Online)
Service Chaining Based on Capacitated Shortest Path Tour Problem -- Solution Based on Deep Reinforcement Learning and Graph Neural Network --
Takanori Hara, Masahiro Sasabe (NAIST) NS2022-2
The service chaining problem is one of the resource allocation problems in network functions virtualization (NFV) networ... [more] NS2022-2
pp.7-12
MSS, NLP 2022-03-28
13:00
Online Online A Study on Applying Game Balancing Method Using Deep Reinforcement Learning to Pokemon
Ryohei Okamura, Atsuo Ozaki (OIT) MSS2021-61 NLP2021-132
We propose a method to automatically adjust the game balance of video games using rein-forcement learning. The problem w... [more] MSS2021-61 NLP2021-132
pp.33-36
MSS, NLP 2022-03-29
10:05
Online Online Relationship between Computational Performance and Task Difficulty of Reinforcement Learning Methods Using Reward Machines
Ryuji Watanabe, Gouhei Tanaka (The Univ. of Tokyo) MSS2021-70 NLP2021-141
In reinforcement learning, it is necessary to take into account the history of past state transitions during learning fo... [more] MSS2021-70 NLP2021-141
pp.77-82
CCS 2022-03-27
17:05
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
Reinforcement-learning based selection of CWmin in IEEE 802.11 networks.
Kosuke Sanada (Mie Univ.) CCS2021-51
This paper proposes Q-learning based selection of contention window minimum value in IEEE 802.11 networks. In the propos... [more] CCS2021-51
pp.90-95
ITS, IEE-ITS 2022-03-11
14:15
Online Online Modeling Right-Turn Driver Behaviour at the Intersection using Reingforcement Learning
Aiichiro Iseki, Tomohiro Kamito, Yuji Matsuki (FIT) ITS2021-69
In this study, we developed a driver model that reflects the characteristics of a driver using reinforcement learning to... [more] ITS2021-69
pp.34-37
WIT, IPSJ-AAC 2022-03-08
14:50
Online Online Improvement and Evaluation of Speech Content Coordinating Mechanism in Intelligent Dialogue Agent -- Toward Development of Comprehensive Preventive Care System --
Sho Hirose, Daisuke Kitakoshi (NIT, Tokyo College), Kentaro Suzuki (Kyorin Univ.), Masato Suzuki (NIT, Tokyo College) WIT2021-49
Our research group has been developing a Comprehensive Preventive Care System (CPCS) to provide habitual preventive care... [more] WIT2021-49
pp.35-40
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