| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (All Years)
| 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 |
[Return to Top Page]