Development of efficient multi-armed bandit algorithm for good arm identification and its application
| Project/Area Number |
18K18099
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 61030:Intelligent informatics-related
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| Research Institution | Hokkaido University |
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Principal Investigator |
Koji Tabata 北海道大学, 電子科学研究所, 准教授 (20814445)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2021: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2020: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
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| Keywords | 多腕バンディット / 良腕識別 / 分類バンディット / アルゴリズム / 機械学習 / 多腕バンディット問題 / 良腕識別問題 |
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| Outline of Final Research Achievements |
The purpose of this research is development and application of efficient methods to identify good arms, whose expected reward is larger then a given threshold, under the multi-armed bandit setting which is a model of trade-off between knowledge exploration and exploitation. Here, an efficient method means that it can identify the good arm as few samples as possible.
We confirmed that our proposed methods have better performance then exiting method. We have also developed a prototype diagnostic device using the algorithm developed in this research.
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| Academic Significance and Societal Importance of the Research Achievements |
学術的意義としては、病理診断に応用することを考慮した新しい問題設定とそのための良腕探索アルゴリズムの開発を行った。本研究により開発された手法は、病理診断だけではなく、品質保証、品質管理、創薬などへも応用可能である。
また、情報計測の分野にとって避けられない偽陽性・偽陰性が扱えるように、多腕バンディットアルゴリズムの平均報酬にバイアスが存在するような設定を新規に開拓した。
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Report
(5 results)
Research Products
(8 results)
