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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IN, RCS, NV (Joint) |
2024-05-31 14:15 |
Fukuoka | Fukuoka University | A Multi-Agent Reinforcement Learning Deployment Method for Multiple UAVs Jin Nakazato (UTOKYO), Gia Khanh Tran (TokyoTech), Katsuya Suto (UEC) |
(To be available after the conference date) [more] | |
| AI | 2024-03-01 13:40 |
Aichi | Room0221, Bldg.2-C, Nagoya Institute of Technology | Applying Graph Neural Networks and Reinforcement Learning to the Multiple Depot-Multiple Traveling Salesman Problem Dongyeop Kim, Toshihiro Matsui (NITech)  AI2023-39 |
In this study, we introduce a method combining Graph Neural Networks (GNN) and reinforcement learning for the Multiple D... [more] | AI2023-39 pp.13-18 |
| NS, IN (Joint) |
2024-03-01 11:35 |
Okinawa | Okinawa Convention Center | Application of a Deep Reinforcement Learning Algorithm to Virtual Machine Migration Control in Multi-Stage Information Processing Systems Yuki Kojitani (Okayama Univ.), Kazutoshi Nakane (Nagoya Univ.), Yuya Tarutani (Okayama Univ.), Celimuge Wu (UEC), Yusheng Ji (NII), Tokumi Yokohira (Okayama Univ.), Tutomu Murase (Nagoya Univ.), Yukinobu Fukushima (Okayama Univ.) IN2023-87 |
This paper tackles a virtual machine (VM) migration control problem to maximize the progress (accuracy) of information p... [more] | IN2023-87 pp.130-135 |
| MSS, CAS, IPSJ-AL [detail] | 2023-11-16 16:30 |
Okinawa | Deep Reinforcement Learning for Multi-Agent Systems with Temporal Logic Specifications Keita Terashima, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) CAS2023-70 MSS2023-40 |
In multi-agent systems, the challenge is how a group of agents collaborate to achieve a common goal. In our previous wor... [more] | CAS2023-70 MSS2023-40 pp.54-58 |
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| HCS, CNR | 2023-11-06 15:30 |
Tokyo | Kogakuin University (Primary: On-site, Secondary: Online) |
Effect of Assertive Feedback from a Job Interview Training Agent Nao Takeuchi, Tomoko Koda (OIT), Miho Hotta (KINDAI) CNR2023-25 HCS2023-87 |
In this study, we developed an interview training system in which a virtual agent provides feedback on improvements in i... [more] | CNR2023-25 HCS2023-87 pp.96-101 |
| AI | 2023-09-12 14:15 |
Hokkaido | Agent Strategy Introduced Dynamic Price Adjustment by Transaction Status and Statistics for Supply Chain Management Ryoga Miyajima, Katsuhide Fujita (TUAT) AI2023-14 |
Automatic negotiation is attracting attention as a means of agreement-making in multi-agent systems. The International A... [more] | AI2023-14 pp.72-76 |
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| AI | 2023-09-12 14:15 |
Hokkaido | A Study of Distributed Constraint Optimization for Publish/Subscribe Messaging Platforms Toshihiro Matsui (Nitech) AI2023-27 |
Optimization problems and solution methods on multiagent systems have been studied as basis of distributed resource allo... [more] | AI2023-27 pp.157-160 |
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| MVE | 2023-09-08 15:10 |
Osaka | (Primary: On-site, Secondary: Online) |
Interview dialogue system based on the evaluation grid method using large-scale language models Daisuke Miyajima, Fan Zhang, Masashi Sugimoto, Kanon Sasaki, Taisei Kitano (Kwansei Gakuin Univ.), Sho Hashimoto (Seinan Gakuin univ./Kwansei Gakuin Univ.), Noriko Nagata (Kwansei Gakuin Univ.) MVE2023-20 |
The individual interview method using the evaluation grid method is known as a method for structurally understanding use... [more] | MVE2023-20 pp.33-38 |
| HCS | 2023-08-26 14:30 |
Hyogo | (Primary: On-site, Secondary: Online) |
SPARKIT: A Multi-Agent Mind-Map Generation System for Idea Generation Masaki Ishizaka (AGU), Akihito Taya (UTokyo), Yoshito Tobe (AGU) HCS2023-54 |
The demand for novel ideas in a wide range of fields, such as product development, marketing, and academic research, has... [more] | HCS2023-54 pp.64-69 |
| MSS, CAS, SIP, VLD | 2023-07-07 09:30 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Proposal and Evaluation of Distributed Formation Method based on a Cyclic Pursuit Strategy Anna Fujioka, Masaki Ogura, Naoki Wakamiya (Osaka Univ.) CAS2023-15 VLD2023-15 SIP2023-31 MSS2023-15 |
A system consisting of a large number of agents that make decisions autonomously is called a multi-agent system. These s... [more] | CAS2023-15 VLD2023-15 SIP2023-31 MSS2023-15 pp.72-77 |
| NLP, MSS | 2023-03-16 15:05 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Evaluation of Cooperative Evacuation Guidance Methods for Large-Scale Events Chihiro Yamada, Atsuo Ozaki (OIT) MSS2022-88 NLP2022-133 |
In recent years, natural disasters such as earthquakes have been increasing in many parts of the world. Therefore, effec... [more] | MSS2022-88 NLP2022-133 pp.122-125 |
| NLP, MSS | 2023-03-17 10:00 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Development and Evaluation of A Leader Based Swarm Guidance Algorithm Inspired by Farthest Agent Targeting Method Kei Akiguchi, Masaki Ogura, Aiyi Li, Naoki Wakamiya (Osaka Univ.) MSS2022-94 NLP2022-139 |
We consider the problem of guiding and controlling a multi-agent system. We assume that an external agent with an attrac... [more] | MSS2022-94 NLP2022-139 pp.150-155 |
| RCC, ISEC, IT, WBS | 2023-03-14 13:00 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
On Reward Distribution in Reinforcement Learning of Multi-Agent Surveillance Systems with Temporal Logic Specifications Keita Terashima, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) IT2022-81 ISEC2022-60 WBS2022-78 RCC2022-78 |
In multi-agent systems, it is important to design a reward distribution method based on the contribution of agents for e... [more] | IT2022-81 ISEC2022-60 WBS2022-78 RCC2022-78 pp.86-90 |
| RCC, ISEC, IT, WBS | 2023-03-15 09:30 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Design Using Sparse Optimization of Consensus Dynamics in High-Order Multi-Agent Systems Ryosuke Adachi, Yuji Wakasa (Yamaguchi Univ.) IT2022-107 ISEC2022-86 WBS2022-104 RCC2022-104 |
This work considers the consensus problem of multi-agent systems with high-order dynamics. When the dynamics of each age... [more] | IT2022-107 ISEC2022-86 WBS2022-104 RCC2022-104 pp.248-250 |
| RCC, ISEC, IT, WBS | 2023-03-15 09:55 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Control of Multi-robot Systems Using A Future Map Aki Matsutaka (Nagoya Univ.), Shun-ichi Azuma (Kyoto Univ.), Ryo Ariizumi, Toru Asai (Nagoya Univ.) IT2022-108 ISEC2022-87 WBS2022-105 RCC2022-105 |
This research was presented at "the 66th Conference of the Institute of Systems, Control and Information Engineers" and ... [more] | IT2022-108 ISEC2022-87 WBS2022-105 RCC2022-105 pp.251-256 |
| AI, JSAI-KBS, JSAI-SAI, JSAI-DOCMAS, IPSJ-ICS (Joint) |
2023-03-11 16:15 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Analysis of Process of Pluralistic Ignorance Using the Social Feedback Model Taisei Ninomiya, Fujio Toriumi (u-Tokyo), Hitoshi Yamamoto (RIS) AI2022-53 |
This study aims to analyze the factors and processes of occurrence, continuing, and resolution of pluralistic ignorance ... [more] | AI2022-53 pp.30-35 |
| HCS | 2023-03-03 13:40 |
Shizuoka | Tokoha University（KusanagiCampus） (Primary: On-site, Secondary: Online) |
Agent-based Modeling Estimation of Personal Intentions and Behavior in Small Group Decision-Making Shota Shiiku, Yugo Takeuchi (Shizuoka Univ.) HCS2022-94 |
In general, in the decision-making process of small groups, there are many opportunities for members to explicitly expre... [more] | HCS2022-94 pp.106-111 |
| CAS, CS | 2023-03-01 10:45 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Introduction IoT Indoor Evacuation Guidance System into Indoor Evacuation Simulation with Network Model Kota Ishisaka, Shunya Nakada, Nao Ito (NITT) CAS2022-99 CS2022-76 |
In Japan, many disasters have occurred due to natural conditions such as earthquakes and typhoons. In such cases, there ... [more] | CAS2022-99 CS2022-76 pp.18-22 |
| EST | 2023-01-27 10:10 |
Okinawa | (Primary: On-site, Secondary: Online) |
Research on Dynamic Grouping System for STEAM Education
-- Effectiveness verification with GPS-equipped tablet devices -- Aya Kojima, Hideaki Kimura (Chubu Univ.) EST2022-91 |
In recent years, due to the accelerating progress of computer performance, research and development of systems that link... [more] | EST2022-91 pp.88-91 |
| AI | 2022-12-21 16:50 |
Fukuoka | Distributed Action Planning and Execution with fluctuated movement for Iterative Multi-agent Path Planning Yuki Miyashita (Shimizu Corp.), Tomoki Yamauchi, Toshiharu Sugawara (Waseda Univ) AI2022-46 |
This study proposes a distributed planning method with asynchronous execution for the multi-agent pick up and delivery (... [more] | AI2022-46 pp.74-79 |
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