| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Outline of Final Research Achievements |
With the increasing amount of data and the progress in robotics, it is one of the urgent issues to establish a more efficient action selection algorithm while it learns causal relationship under uncertainty. In this study, we prove the effectiveness of a value function, the loosely symmetric (LS) model, that models the causal intuition of humans. In the multi-armed bandit problems, robotic action acquisition task, and Monte Carlo tree search, we showed the efficiency realized by the LS model. We also generalized the model loosening the original restrictions based on new analyses, and tested its cognitive validity by a meta-analysis and experiments.
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