Dynamic Robust Team Formation
| Project/Area Number |
17H01790
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Kobe University |
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Principal Investigator |
Okimoto Tenda 神戸大学, 海事科学研究科, 准教授 (10632432)
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| Co-Investigator(Kenkyū-buntansha) |
平山 勝敏 神戸大学, 海事科学研究科, 教授 (00273813)
井上 克巳 国立情報学研究所, 情報学プリンシプル研究系, 教授 (10252321)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥13,780,000 (Direct Cost: ¥10,600,000、Indirect Cost: ¥3,180,000)
Fiscal Year 2020: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2019: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2018: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2017: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
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| Keywords | マルチエージェントシステム / チーム編成 / 提携構造形成 / ロバスト性 / 不確実性 / 協力ゲーム / ロバスト / 提携ゲーム / スケジューリング / レジリエンス / 人工知能 |
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| Outline of Final Research Achievements |
How to form a team for achieving a given set of tasks is an important issue in multi-agent systems. Team formation (i.e. set covering problem) is the problem of selecting a group of agents, where each agent is characterized by a set of capabilities; the objective is to achieve a given set of tasks, where each task is made precise by a set of capabilities necessary for managing it. In this work, we investigated the theoretical work for the robust team formation. Additionally, we studied the coalition formation problem (i.e. set partitioning problem) which involves partitioning a set of agents into coalitions so that the social surplus is maximized. Several papers are accepted in top conferences and top journal. Also, we obtained several best paper awards for our research. Finally, DAMT formation and nurse and sport scheduling problems are also investigated as our application problems.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は，チーム編成問題において多目的最適化及び動的環境を考慮した点が新しく，特に，ロバスト性を考慮したチーム編成・提携構造形成や，これらの問題を動的環境へと拡張した研究は寡聞にして見当たらない．本研究の発展により，動的環境の変化及びロバスト性を考慮した，より現実的なチーム編成・提携構造形成問題の定式化が可能となり，人工知能・計算機科学をはじめ，経済学，工学（制御），生態学等の様々な方面への展開が期待できる．自然災害や人災に対してロバスト性を考慮することは重要な問題であり，本研究は，その基盤となる理論的研究を実現しており，今後，多くの研究分野で展開されると考える．
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Report
(5 results)
Research Products
(48 results)
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[Journal Article] Probabilistic Coalition Structure Generation2018
Author(s)
Nicolas Schwind, Tenda Okimoto, Katsutoshi Hirayama, Katsumi Inoue, Jean-Marie Lagniez, Pierre Marquis
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Journal Title
In proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018)
Volume: -
Pages: 663-664
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] Robust Coalition Structure Generation2018
Author(s)
Tenda Okimoto, Nicolas Schwind, Emir Demirovic, Katsumi Inoue, Pierre Marquis
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Journal Title
In: Proceedings of the 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2018), Lecture Notes in Computer Sciencei
Volume: 11224
Pages: 140-157
DOI
ISBN
9783030030971, 9783030030988
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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