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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
| 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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| 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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| 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 | 2023-03-17 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 |
| 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 |
| RCC, ITS, WBS | 2022-12-13 14:45 |
Shiga | Ritsumeikan Univ. BKC (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Cloud-mediated self-triggered control of a linear multi-agent system Takumi Namba, Kiyotsugu Takaba (Ritsumeikan Univ.) WBS2022-37 ITS2022-13 RCC2022-37 |
In this presentation, we propose a self-triggered synchronization control method of a general high-order linear multi-ag... [more] | WBS2022-37 ITS2022-13 RCC2022-37 pp.19-20 |
| RCC, ITS, WBS | 2022-12-14 14:45 |
Shiga | Ritsumeikan Univ. BKC (Primary: On-site, Secondary: Online) |
Characterization of consensus value in consensus control driven by value exchange Daiki Sugiyama (Nagoya Univ.), Shun-ichi Azuma (Kyoto Univ.), Ryo Ariizumi, Toru Asai (Nagoya Univ.) WBS2022-50 ITS2022-26 RCC2022-50 |
This paper deals with consensus control in multi-agent systems driven by value exchange. In this system, agents own toke... [more] | WBS2022-50 ITS2022-26 RCC2022-50 pp.89-92 |
| IT, ISEC, RCC, WBS | 2022-03-10 14:15 |
Online | Online | Distributed Online Optimization under Inequality Constraints on Directed Open Multi-agent Systems Riki Sawamura, Naoki Hayashi, Masahiro Inuiguchi (Osaka Univ.) IT2021-108 ISEC2021-73 WBS2021-76 RCC2021-83 |
Distributed optimization in multi-agent systems has attracted attention in various fields. In this study, we consider a ... [more] | IT2021-108 ISEC2021-73 WBS2021-76 RCC2021-83 pp.150-154 |
| SS, MSS | 2022-01-11 16:40 |
Nagasaki | Nagasakiken-Kensetsu-Sogo-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
Study on Stability of Distributed Scheduling Using Alternating Direction Method of Multipliers Naoki Niiya, Toshiyuki Miyamoto (Osaka Univ.), Daichi Inoue, Toyohiro Umeda (KOBELCO), Shigemasa Takai (Osaka Univ.) MSS2021-42 SS2021-29 |
In recent years, the development of optimization methods in multi-agent systems has been remarkable. We have proposed a ... [more] | MSS2021-42 SS2021-29 pp.64-69 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-14 16:35 |
Online | Online | [Invited Talk]
Optimal Control of Multi-Agent Systems: Surveillance Problem and Vehicle Platooning Koichi Kobayashi (Hokkaido Univ.) RCC2021-29 NS2021-39 RCS2021-84 SR2021-27 SeMI2021-15 |
In this talk, our results on control of multi-agent systems are introduced. First, the surveillance problem is introduce... [more] | RCC2021-29 NS2021-39 RCS2021-84 SR2021-27 SeMI2021-15 p.36(RCC), p.38(NS), p.38(RCS), p.41(SR), p.20(SeMI) |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 13:50 |
Online | Online | Simplification of Average Consensus Algorithm in Distributed HALS Algorithm for NMF Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-3 IBISML2021-3 |
Nonnegative Matrix Factorization (NMF) is the process of approximating a given nonnegative matrix by the product of two ... [more] | NC2021-3 IBISML2021-3 pp.15-22 |
| NLP, MSS (Joint) |
2021-03-16 09:40 |
Online | Online | Pinning consensus control of a group of quadrotors modeled by a directed acyclic graph Akinori Sakaguchi, Toshimitsu Ushio (Osaka Univ.) MSS2020-50 |
In this study, we consider a pinning consensus control problem with a given altitude for a group of heterogeneous quadro... [more] | MSS2020-50 pp.33-36 |
| MSS, NLP (Joint) |
2020-03-10 16:45 |
Aichi | (Cancelled but technical report was issued) |
Reinforcement Learning Based Multi-Ship Course Search Method with Tracking Control Hiroki Kimura, Takahiro Tomihara, Takeshi Kamio (Hiroshima City Univ.), Takahiro Tanaka (Japan Coast Guard Academy), Kunihiko Mitsubori (Takushoku Univ.), Hisato Fujisaka (Hiroshima City Univ.) NLP2019-131 |
We have developed multi-agent reinforcement learning system (MARLS) to search ships’ courses. Since the rudder angle is ... [more] | NLP2019-131 pp.103-108 |
| RCC | 2020-01-27 14:10 |
Osaka | Distributed online subgradient method over unbalanced directed graphs Makoto Yamashita, Naoki Hayashi, Takeshi Hatanaka, Shigemasa Takai (Osaka Univ.) RCC2019-72 |
This paper considers a constrained distributed online optimization problem over strongly connected unbalanced directed n... [more] | RCC2019-72 pp.13-18 |
|
| AI | 2019-12-06 13:10 |
Overseas | The University of Adelaide | Multi-Issue Negotiation Protocol with Pre-Domain Narrowing Yuta Hosokawa, Ryohei Kawata, Katsuhide Fujita (TUAT) AI2019-38 |
The size of the negotiation domain affects calculation costs and efficiency on Automated negotiation. This study propose... [more] | AI2019-38 pp.1-4 |
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