2017 Fiscal Year Final Research Report
Learning algorithm and neural basis of reducing market anomalies
| Project/Area Number |
15H03124
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Basic / Social brain science
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| Research Institution | Tamagawa University |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
KOIKE Yasuharu 東京工業大学, 科学技術創成研究院, 教授 (10302978)
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| Research Collaborator |
MATSUMORI Kaosu
YOMOGIDA Yukihito
IIJIMA Kazuki
AOKI Ryuta
IZUMA Keise
SUZUKI Shinsuke
MURAYAMA Kou
SAKAKI Michiko
FOO Jerome
SUGIURA Ayaka
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Keywords | ニューロエコノミクス / 認知バイアス / 学習アルゴリズム / 脳 |
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| Outline of Final Research Achievements |
We proposed an exponentially biased Bayesian update model with its underlying neural circuits, which can explain most cognitive biases in human probability judgments as well as electrophysiological findings on experimental animals. The model also provides a unified account for some psychiatric diseases. We applied the model to determine the learning algorism to diminish the cognitive bias in an experimentally designed market. In addition, we proposed a new behavior change theory that is consistent to the findings in behavioral economics.
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| Free Research Field |
認知神経科学
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