| Budget Amount *help |
¥44,980,000 (Direct Cost: ¥34,600,000、Indirect Cost: ¥10,380,000)
Fiscal Year 2021: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2020: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2019: ¥10,660,000 (Direct Cost: ¥8,200,000、Indirect Cost: ¥2,460,000)
Fiscal Year 2018: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2017: ¥11,700,000 (Direct Cost: ¥9,000,000、Indirect Cost: ¥2,700,000)
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| Outline of Final Research Achievements |
In this research, we developed theories and algorithms for sqeuential decision making and probabilistic inference. In the study of reinforcement learning, we developed methods for weakly supervised imitation learning and hierarchization of complex problems to improve their practicality, and demonstrated their effectiveness experimentally. For multi-arm bandit problems, we developed algorithms with theoretical guarantees for linear bandit, dueling bandit, good-arm identification, and combinatorial bandit. In the area of probabilistic inference, we have conducted research on making Bayesian inference robust, speeding up approximate computation, and modeling temporal events, and have verified the effectiveness of these methods both theoretically and experimentally.
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