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2020 – today
- 2023
[c13]Jiaxing Tian, Jun Izawa:
Study on High-Level Structure of cognition control construction in Exploration and Exploitation within Multi-Armed Bandit Model of Reinforcement Learning. MHS 2023: 1-6- 2022
- [j6]Lucas Rebelo Dal'Bello
, Jun Izawa:
Computational role of exploration noise in error-based de novo motor learning. Neural Networks 153: 349-372 (2022) - [j5]Yihao Wu, Masahiko Morita, Jun Izawa:
Reward prediction errors, not sensory prediction errors, play a major role in model selection in human reinforcement learning. Neural Networks 154: 109-121 (2022) - 2021
- [j4]Takahisa Inoue, Shin Terada, Masanori Matsuzaki, Jun Izawa:
A small-scale robotic manipulandum for motor control study with rodents. Adv. Robotics 35(13-14): 898-906 (2021) - [j3]Lucas Rebelo Dal'Bello, Jun Izawa:
Task-relevant and task-irrelevant variability causally shape error-based motor learning. Neural Networks 142: 583-596 (2021) - [c12]Yihao Wu, Jun Izawa:
The Regret Motivated Reinforcement Learning. MHS 2021: 1-5
2010 – 2019
- 2019
- [c11]Ryota Ishikawa, Kyohei Sasaki, Saho Ayabe-Kanamura, Jun Izawa:
Learning to control the other's body facilitates the embodied perspective taking. CogSci 2019: 3287 - 2018
- [c10]Jun Izawa:
Application of computational neuroscience to robotic rehabilitation: a conceptual study. MHS 2018: 1-2 - 2017
- [c9]Tomohiro Tanno, Kazumasa Horie, Jun Izawa, Masahiko Morita:
Robustness of Selective Desensitization Perceptron Against Irrelevant and Partially Relevant Features in Pattern Classification. ICONIP (6) 2017: 520-529 - 2015
- [c8]Jun Ota, Hajime Asama, Toshiyuki Kondo, Hirokazu Tanaka, Shiro Yano, Jun Izawa, Shinya Aoi, Ryosuke Chiba:
Modeling method in embodied-brain systems science. MHS 2015: 1-2 - [c7]Daichi Sasaki, Jun Izawa, Masahiko Morita:
A computational approach to detect a mete-learning of the cortical basis function during a motor adaptation study. MHS 2015: 1-5 - 2014
- [c6]Hiroshi Yokoyama, Isao Nambu, Jun Izawa, Yasuhiro Wada:
Temporal changes of beta rhythms and rotation-related negativity reflect switches in motor imagery. EMBC 2014: 1326-1329 - 2012
- [c5]Yohei Takata, Toshiyuki Kondo, Midori Saeki, Jun Izawa, Kotaro Takeda, Yohei Otaka, Koji Ito:
Analysis of extrinsic and intrinsic factors affecting event related desynchronization production. EMBC 2012: 4619-4622 - 2011
- [j2]Jun Izawa, Reza Shadmehr:
Learning from Sensory and Reward Prediction Errors during Motor Adaptation. PLoS Comput. Biol. 7(3) (2011)
2000 – 2009
- 2006
- [c4]Jun Izawa, Takahiro Shimizu, Toshiyuki Aodai, Toshiyuki Kondo, Hiroaki Gomi, Shigeki Toyama, Koji Ito:
MR Compatible Manipulandum with Ultrasonic Motor for fMRI Studies. ICRA 2006: 3850-3854 - 2004
- [j1]Jun Izawa, Toshiyuki Kondo, Koji Ito:
Biological arm motion through reinforcement learning. Biol. Cybern. 91(1): 10-22 (2004) - 2003
- [c3]Jun Izawa, Toshiyuki Kondo, Koji Ito:
Motor learning model using reinforcement learning with neural internal model. ICRA 2003: 3146-3151 - 2002
- [c2]Jun Izawa, Toshiyuki Kondo, Koji Ito:
Biological Robot Arm Motion through Reinforcement Learning. ICRA 2002: 3398-3403 - 2001
- [c1]Koji Ito, Jun Izawa, Toshiyuki Kondo:
Motor learning and control based on the internal model. CDC 2001: 21-26
Coauthor Index
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