| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Outline of Final Research Achievements |
Recently, studies using complex models representing uncertainties of the uncertainty degrees are popular. However, such a model requests a lot of effort from human experts to provide various information in modelling. In this study, we demonstrate that simple uncertainty models requesting much less information can work well and effectively for representing human preferences in the settings of optimization and decision-making problems. Moreover, we show that models retaining the uncertainty existing in the given data and information are advantageous for the specification of tolerance and privacy protection in decision analysis and rule induction、respectively.
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