Integrating multi-objective optimization, cooperative problem solving and system design for preferences of multiple participants
| Project/Area Number |
16K00301
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Nagoya Institute of Technology |
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Principal Investigator |
Matsui Toshihiro 名古屋工業大学, 工学(系)研究科(研究院), 准教授 (60437093)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | マルチエージェントシステム / 協調問題解決 / 多目的最適化 / 公平性 / 学習 |
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| Outline of Final Research Achievements |
We addressed the integration of cooperative problem solving, system design and reinforcement learning methods for practical problems including collaboration assistance or routing problems considering the preference among members or residents, where the unfairness among participants should be improved.
We investigated (1) a framework based on interactive multi-objective optimization methods for multiple parties, (2) learning methods to obtain optimal routes or policies considering fairness among members related to unknown environments, and (3) relaxation and stochastic local search algorithms to improve the fairness for large-scale problems. The proposed methods are experimentally evaluated with several example problems including a nurse scheduling problem with individual preferences and a route optimization with environmental costs for partial areas.
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| Academic Significance and Societal Importance of the Research Achievements |
学術的意義: 多目的最適化，協調問題解決，制度設計，行動規則の学習を融合した，新たな問題と解法の模索，参加者の公平性と主体性を重視する最適化手法の検討に本研究の特色があり，このような最適化の枠組と，実際的かつ大規模な系に適用する方法の一端を明らかとしたことに，学術的な意義がある．
社会的意義: 近年のサービスにおける多数の参加者からなるコラボレーション支援やネットワーク上の電力，交通，施設等の資源の割り当てにおいては，個々の参加者の利益やコストの水準を維持する利害調整を考慮しつつ意思決定を行うための協調的な最適化手法が求められており，その基礎検討としての社会的意義がある．
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Report
(4 results)
Research Products
(28 results)
