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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IN, NS (Joint) |
2023-03-02 13:30 |
Okinawa | Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
Online Deep Reinforcement Learning for Network Slice Reconfiguration under Variable Number of Service Function Chains Kairi Tokuda, Takehiro Sato, Eiji Oki (Kyoto Univ.) |
(To be available after the conference date) [more] | |
| HCS | 2023-03-03 13:10 |
Shizuoka | Tokoha University（KusanagiCampus） (Primary: On-site, Secondary: Online) |
Study on the resilient role in coordinated behavior of a triad using deep reinforcement learning and rule-based modeling Jun Ichikawa (Shizuoka Univ.), Kazushi Tsutsui, Keisuke Fujii (Nagoya Univ.) |
(To be available after the conference date) [more] | |
| DC | 2023-02-28 14:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg (Primary: On-site, Secondary: Online) |
Test Point Selection Method Using Graph Neural Networks and Deep Reinforcement Learning Shaoqi Wei, Kohei Shiotani, Senling Wang, Hiroshi Kai, Yoshinobu Higami, Hiroshi Takahashi (Ehime Univ.) |
(To be available after the conference date) [more] | |
| SeMI, IPSJ-UBI, IPSJ-MBL | 2023-03-01 16:40 |
Aichi | (Primary: On-site, Secondary: Online) |
Study of Deep Reinforcement Learning for Wireless Multihop Networks Cui Zhihan, Khun Aung thura phyo, Lim Yuto, Tan Yasuo (JAIST) |
[more] | |
| NC, NLP | 2023-01-29 14:25 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Continuous Value Control of Robot with Reservoir Actor-Critic Model Koutaro Minato, Yuichi Katori (Future Univ Hakodate)  NLP2022-103 NC2022-87 |
Deep learning is expected to be utilized to control robots operating in complex environments, but this requires a large ... [more] | NLP2022-103 NC2022-87 pp.118-122 |
| CQ, CBE (Joint) |
2023-01-26 14:00 |
Ibaraki | Epochal Tsukuba International Congress Center (Primary: On-site, Secondary: Online) |
A Power-Saving and Load-Balancing Oriented Autonomous Decentralized Network Protocol Using Wake-up Radio for Wireless Sensor Networks Ryota Horiuchi, Nobuyoshi Komuro (Chiba Univ.) CQ2022-67 |
We propose a power-saving and load-balancing oriented autonomous decentralized cross-layer protocol for wireless sensor ... [more] | CQ2022-67 pp.35-40 |
| SeMI, SeMI (Joint) |
2023-01-19 14:10 |
Tokushima | Naruto grand hotel (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study of Joint Control Method of Wireless LAN and Machine Learning Settings for Communication-efficient Split Computing Kojin Yorita, Takayuki Nishio (Tokyo Tech), Daiki Yoda, Toshihisa Nabetani (Toshiba) SeMI2022-77 |
Split computing (SC) enables machine learning (ML) inference with a deep neural network on resource-constrained devices.... [more] | SeMI2022-77 pp.28-29 |
| IBISML | 2022-12-22 16:35 |
Kyoto | Kyoto University (Primary: On-site, Secondary: Online) |
Implementation and evaluation of NoisyNets to Reinforcement learning of Automated Designing ICT System Tianchen Zhou (Sophia Univ.), Yutaka Yakuwa (NEC), Natsuki Okamura (Sophia Univ.), Takayuki Kuroda (NEC), Ikuko E. Yairi (Sophia Univ.) IBISML2022-50 |
This paper introduces a reinforcement learning method for the ICT system design process. Since the state space of the de... [more] | IBISML2022-50 pp.46-53 |
| AI | 2022-12-21 16:30 |
Fukuoka | Agent based Modeling and Reinforcement Learning for optimal allocation of resources Rashmi Tilak, Toshiharu Sugawara (Waseda University) AI2022-45 |
We propose a model and notation for business process for delivery of parcels using drones and attempt to improve the tot... [more] | AI2022-45 pp.68-73 |
|
| DC | 2022-12-16 15:00 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Learning of train control measures by means of Deep Q-Network
-- Preliminary study with a single train control -- Shogo Igarashi, Takumi Fukuda, Sei Takahashi, Hideo Nakamura (Nihon Univ), Tetsuya Takata (Kyosan Electric Manufacturing) DC2022-77 |
Although the predictive fuzzy control technique has been put to practical use as a train control strategy for automatic ... [more] | DC2022-77 pp.26-29 |
| HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa | Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Emergence of Agent Exemplary Behavior by Reinforcement Learning in Mobility Tasks Yudai Harada, Yugo Takeuchi (Shizuoka Univ.) |
Humans can show high adaptability in a short period of time to unknown tasks and environments they enter for the first t... [more] | |
| MBE, NC | 2022-12-03 14:45 |
Osaka | Osaka Electro-Communication University | Acquisition process of value evaluation criteria of a reinforcement learning agent with embodiment and intrinsic motivation in drawing Yoshia Abe, Shogo Yonekura, Yoshiyuki Ohmura, Yasuo Kuniyoshi (UTokyo) MBE2022-38 NC2022-60 |
A part of a human's aesthetic sense can be acquired through experience. However, little is known about the mechanism of ... [more] | MBE2022-38 NC2022-60 pp.74-79 |
| RISING (3rd) |
2022-10-31 10:30 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Validation of a Low Latency Method for Wireless LANs using Reinforcement Learning in a Thermal Power Plant Environment Daiki Yoda, Toshihisa Nabetani (Toshiba) |
In industry, the demand for wireless communications is increasing, and especially in control communication applications,... [more] | |
| RISING (3rd) |
2022-10-31 10:30 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Making a Pre-training Model of Deep Reinforcement Learning for TCP Congestion Control using Different Communication Environments Takumi Odagawa, Satoshi Ohzahata, Ryo Yamamoto (UEC) |
Congestion control is becoming more important as network usage increases. In recent years, congestion controls using Dee... [more] | |
| RISING (3rd) |
2022-10-31 13:00 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Learning-based Environment Adaptive Wireless MAC Protocol Design Koshiro Aruga, Takeo Fujii (UEC) |
With the Internet of Things (IoT) era, the number of devices that communicate wirelessly has been rapidly increasing. In... [more] | |
| RISING (3rd) |
2022-10-31 14:00 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Performance Evaluation on 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] | |
| 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) |
Bluetooth Low Energy (BLE) has been applied to various IoT applications due to the popularization of Bluetooth-enabled d... [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 |
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