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Keynote Talk 3
Kenji Doya, Okinawa Institute of Science and Technology, Japan
The basic process of decision-making can be captured by learning of action values according to the theory of reinforcement learning. In our daily life, however, we rarely rely on pure trial-and-error and utilize any prior knowledge about the world to imagine what situation will happen before taking an action. How such ”mental simulation” is realized in the circuit of the brain is an exciting new topic of neuroscience. Here I report our works with functional MRI in humans and two-photon imaging in mice to clarify how action-dependent state transition models are learned and utilized in the brain.
Bio sketch Kenji Doya is a Professor of Neural Computation Unit, Okinawa Institute of Science and Technology (OIST) Graduate University. He took his PhD in 1991 at the University of Tokyo and worked as a postdoc at U. C. San Diego and the Salk Institute. In 1994, he joined Advanced Telecommunications Research International (ATR) as a Senior Researcher and then served as a Group Leader of Kawato Dynamic Brain Project. In 2004, he was appointed as a Principal Investigator of the OIST Initial Research Project and started Okinawa Computational Neuroscience Course (OCNC) as the chief organizer. As OIST established itself as a Graduate University in 2011, he became a Professor and served as the Vice Provost for Research. He is interested in reinforcement learning in both natural and artificial creatures. He has served as a Co-Editor in Chief of Neural Networks from 2008 to 2021 and a board member of International Neural Network Society (INNS), Japanese Neural Network Society (JNNS) and Japan Neuroscience Society (JNSS). He serves as the Chairperson of Neuro2022 conference in Okinawa. He received INNS Donald O. Hebb Award in 2018, JNNS Academic Award, APNNS Outstanding Achievement Award, and the age-group 2nd place at Ironman Taiwan in 2019.