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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 31  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SR 2022-01-25
14:40
Online Online Performance Evaluation of Access Control and Transmission Datarate Adaptation using Redundant Check Information for IEEE 802.11ax Wireless LAN
Kazuto Yano, Kenta Suzuki, Babatunde Ojetunde (ATR), Koji Yamamoto (Kyoto Univ.) SR2021-81
In order to meet increasing traffic load on wireless communication, the authors have conducted research and development ... [more] SR2021-81
pp.103-110
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
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
CQ, MIKA
(Joint)
2021-09-09
10:05
Online Online Load balancing method using reinforcement learning between edge and cloud
Hiroki Kobari, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-38
Recently, edge computing has attracted more and more attention. Compared with traditional cloud computing, edge computin... [more] CQ2021-38
pp.6-10
RCS 2019-06-21
11:10
Okinawa Miyakojima Hirara Port Terminal Building Interference Control of LTE-LAA using Q-learning with HARQ
Kenshiro Wada, Tomoaki Ohtsuki (Keio Univ.) RCS2019-91
As a means of high-speed and large-capacity communication, broadbandization of LTE communication is considered.
Howeve... [more]
RCS2019-91
pp.315-320
CS, CQ
(Joint)
2019-04-19
10:25
Osaka Osaka Univ. Library Introduction of Q-Learning to Fixed Assignment based Window Access Scheme with Capture(FAWAC)
Yuki Uehara, Megumi Saito, Shigeru Shimamoto (Waseda Univ.) CS2019-10
This paper presents the effects of applying Q-learning to fixed assignment based window access scheme with capture, such... [more] CS2019-10
pp.51-54
RCS, SR, SRW
(Joint)
2019-03-08
09:50
Kanagawa YRP [Invited Lecture] A Reinforcement Learning Framework for User-to-Access Points Association in Future Wireless Networks
Megumi Kaneko, Thi Ha Ly Dinh (NII), Keisuke Wakao, Hirantha Abeysekera, Yasushi Takatori (NTT) RCS2018-322
This work investigates the issue of distributed user-to-multiple Acess Points (AP) association, where a user requiring s... [more] RCS2018-322
p.205
SR 2018-10-30
10:30
Overseas Mandarin Hotel, Bangkok, Thailand [Poster Presentation] Q-Leaning based Cell Zooming for Energy-Harvesting Small Cell Networks
Katsuya Suto (UEC), Masashi Wakaiki (Kobe Univ.) SR2018-62
With the dense deployment of small cell base stations (SBSs), the radio access network can boost spectrum efficiency. To... [more] SR2018-62
pp.9-10
SR, RCS
(Joint)
(2nd)
2018-10-30
10:30
Overseas Mandarin Hotel, Bangkok, Thailand [Poster Presentation] Multi-agent Trust Evaluation in Vehicular Internet of Things
Celimuge Wu, Tsutomu Yoshinaga (UEC), Yusheng Ji (NII)
We propose a decentralized trust management scheme for vehicular networks. The proposed scheme uses a fuzzy logic-based ... [more]
SAT, WBS
(Joint)
2018-05-25
09:30
Kagoshima Kagoshima University A Study on Resource Allocation Utilizing Q-Learning for Video Transmission in Multiple UAS Networks
Saki Tashiro, Yuichi Kawamoto, Hiroki Nishiyama, Nei Kato (Tohoku Univ.) SAT2018-7
In recent years, the number of the use of unmanned aircrafts(UAs) has increased remarkably, and the world market size of... [more] SAT2018-7
pp.31-36
MoNA 2018-01-19
11:15
Kyoto Campus Plaza Kyoto Decentralized WLAN Access Point Selection through Reinforcement Learning
Takuya Nakamura, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ.), Toshihisa Nabetani (TOSHIBA) MoNA2017-51
Many operators provide public wireless LAN services in public places such as stations or cafes. In many cases, a station... [more] MoNA2017-51
pp.57-62
NLC, IPSJ-NL, SP, IPSJ-SLP
(Joint) [detail]
2017-12-20
17:20
Tokyo Waseda Univ. Green Computing Systems Research Organization Trial of Reinforcement Learning to Analyze Command Utterances for In-vehicle Computer
Masato Tokuhisa, Shuhei Kimura (Tottori Univ.) NLC2017-38
This paper reports a trial of reinforcement learning to analyze command utterances for an in-vehicle computer. The compu... [more] NLC2017-38
pp.55-60
AI 2016-12-09
16:40
Oita   Applying reinforcement learning to multi-agent patrolling with priority setting
Harunobu Ozeki, Ayumi Sugiyama, Toshiharu Sugawara (Waseda Univ.) AI2016-21
We propose a multi-agent patrolling method in an environment with priority. Cooperative behavior is required that a team... [more] AI2016-21
pp.49-54
AI 2016-12-09
17:05
Oita   Reinforcement Learning using Filter and Coarse-Grained States in Multiagent Exploration Problems
Takahisa Yutoku, Ayumi Sugiyama, Toshiharu Sugawara (Waseda Univ.) AI2016-22
(To be available after the conference date) [more] AI2016-22
pp.55-60
AI, JSAI-KBS, JSAI-DOCMAS, JSAI-SAI, IPSJ-ICS 2016-03-01
- 2016-03-04
Hokkaido   Efficient distributed search method using Q-learning in an environment with map
Takahisa Yutoku, Ayumi Sugiyama, Toshiharu Sugawara (waseda) AI2015-65
We propose a method for learning cooperative behavior efficiently in a multi-agent system running in an large environmen... [more] AI2015-65
pp.1-6
NC, MBE
(Joint)
2014-03-18
13:20
Tokyo Tamagawa University Acquisition of Cooperative and Competitive Behaviors in a Two-Players Soccer Game
Takao Satou, Kiyoshi Nishiyama (Iwate Univ.) NC2013-137
The acquisition of an autonomous agent's action rule is a very interesting topic in the field of machine learning. The s... [more] NC2013-137
pp.281-286
RCS, SR, SRW
(Joint)
2014-03-03
15:10
Tokyo Waseda Univ. Combined Learning Based Cell Selection and Transmit Power Reduction in Heterogeneous Networks
Toshihito Kudo, Tomoaki Ohtsuki (Keio Univ.) RCS2013-328
Cell range expansion (CRE) expands a pico cell range virtually with bias values, which can make cell edge throughput and... [more] RCS2013-328
pp.133-138
RCS, SIP 2014-01-24
15:15
Fukuoka Kyushu Univ. UE Outage Reduction with Distributed Learning-based Cell Selection in Cell Range Expansion
Toshihito Kudo, Tomoaki Ohtsuki (Keio Univ.) SIP2013-133 RCS2013-303
Cell range expansion (CRE) expands a pico cell range virtually by adding a bias value to the pico received power, instea... [more] SIP2013-133 RCS2013-303
pp.281-286
RCS 2013-10-18
14:00
Tokyo Sophia Univ. Q-Learning Based Cell Selection in Heterogeneous Networks
Toshihito Kudo, Tomoaki Ohtsuki (Keio Univ.) RCS2013-167
Cell range expansion (CRE) expands a pico cell range virtually by adding a bias value to the pico received power, instea... [more] RCS2013-167
pp.145-150
ASN, RCS, NS, SR
(Joint)
2013-07-19
14:30
Shizuoka Hamamatsu Act City A Fuzzy Inference Intelligent Routing Protocol for Vehicular Ad Hoc Networks
Celimuge Wu, Satoshi Ohzahata, Toshihiko Kato (Univ. of Electro-Comm.) ASN2013-84
Due to vehicle movement, limited wireless resources and lossy feature of wireless channels, providing a reliable multi-h... [more] ASN2013-84
pp.201-206
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