| Project/Area Number |
26400215
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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 |
Foundations of mathematics/Applied mathematics
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| Research Institution | Kanagawa University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
中井 達 千葉大学, 教育学部, 教授 (20145808)
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| Co-Investigator(Renkei-kenkyūsha) |
YASUDA Masami 千葉大学, 理学研究科, 名誉教授 (00041244)
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| Research Collaborator |
Alexey Piunovskiy
Francois Dufour
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| Project Period (FY) |
2014-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | マルコフ決定過程 / 推移法則未知 / ベイズ学習 / 推移法則が未知の場合 |
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| Outline of Final Research Achievements |
In this study, we consider the optimization problem of sequential decision processes with unknown transition probabilities. In this model with uncertainty, we formulate an optimization model with interval estimated transition probabilities from the information of observing the states of system. We derived the properties of optimal policies that are based on the representation of interval valued optimization criteria. We also consider Bayesian learning problems as the partially observed optimization problems with uncertain circumstances. In these models, we also deduced the optimization methods for optimal stopping problem and quality control problem in piecewise deterministic processes.
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