About the lecturer
| Yukie Nagai is a Project Professor at the International Research Center for Neurointelligence at the University of Tokyo. She earned her Ph.D. in Engineering from Osaka University in 2004 and subsequently held positions at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she has led the Cognitive Developmental Robotics Lab at the University of Tokyo. Her research encompasses cognitive developmental robotics, computational neuroscience, and assistive technologies for developmental disorders. Dr. Nagai’s pioneering work focuses on the role of predictive processing in the brain, exploring temporal continuity and individual diversity in cognitive development. In recognition of her contributions, she was named among the “World’s 50 Most Renowned Women in Robotics” (Analytics Insight, 2020), “35 Women in Robotics Engineering and Science” (IEEE IROS, 2022), and "Women in Tech 30" (Forbes JAPAN, 2024). | 
Prof. Yukie NAGAI
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Introduction video
AI for Understanding Human Intelligence
Syllabus
| 1 | Subject | AI for Understanding Human Intelligence |
| 2 | Field | Computer science, Robotics, Developmental psychology |
| 3 | Key words | Cognitive developmental robotics, Neural network, Predictive processing, Cognitive development, Neurodiversity |
| 4 | Global Unit | 2 |
| 5 | Lecturer | Yukie NAGAI |
| 6 | Period | June 30 - July 11, 2025 |
| 7 | Time | 13:00 - 14:30 [June 30 - July 4] 13:00 - 18:30 [July 7 - 11] (Japan Standard Time) |
| 8 | Lecture style | In-person (on Hongo Campus) |
| 9 | Evaluation Criteria | Excellent (S) 90–100£¥; Very good (A) 80–89£¥; Good (B) 70–79%; Pass (C) 60–69%; Fail (D) 0–59£¥ |
| 10 | Evaluation methods | ?Lecture: 25% ?Hands-on project: 25% ?Presentation: 25% ?Final report: 25% |
| 11 | Prerequisites | No prior knowledge about artificial intelligence or robotics is required for the lectures. However, basic computational skills for programming and/or data analysis are preferred for the hands-on projects. |
| 12 | Contents | Purpose This course consists of lectures and hands-on projects, through which students learn how to use AI and robots for investigating human intelligence. Students who successfully complete this course will have: ?learned cognitive and neuroscience theories about human intelligence ?learned how to apply computational techniques to investigate human intelligence ?acquired skills to model and analyze human behaviors ?acquired skills to design and conduct cognitive experiments using robots and various technologies¡¡¡¡ ¡¡ Description
Human infants develop a range of cognitive abilities within their first few years of life. While the developmental dynamics of infant behaviors have been closely studied, the neural, bodily, and social mechanisms guiding this development remain largely unknown. In this course, I will introduce AI and robotics approaches to understanding the mechanisms underlying infant development. This approach, known as cognitive developmental robotics, seeks to reveal the principles of human intelligence by creating artificial systems that learn and grow like infants. Unlike traditional analytical approaches in neuroscience, cognitive science, and psychology, this constructive approach offers the potential to uncover a unified principle of intelligence. The course is divided into three parts: lectures, hands-on projects, and presentations. In the first week (Sessions 1-5), I will provide lectures on how AI and robotics can be used to investigate cognitive development. We will explore computational studies using neural networks and humanoid robots to illustrate how neural, bodily, and social mechanisms interact in cognitive development. In the second week (Sessions 6-17), students will engage in hands-on projects to experience the practical challenges of this research. Working in groups, students will address one of the following topics: (a) modeling and analyzing human behaviors using computational techniques, or (b) designing and conducting cognitive experiments using robots and various technologies. In the final sessions (Sessions 18-20), students will present their hands-on projects, discussing how cognitive development theories can be tested through computational approaches, as well as sharing their achievements and insights from the projects. Schedule 1. Introduction to cognitive developmental robotics
2. Predictive processing through brain 3. Predictive processing through body 4. Predictive processing through social interactions 5. Assistive technologies for people with developmental disorders ?Sessions 6-17: Hands-on project (a) Modeling and analyzing human behaviors using computational techniques (b) Designing and conducting cognitive experiments using robots and various technologies ?Sessions 18-20: Presentation Assignments ?Hands-on project: Students divided into groups will address one of the following projects:
(a) Modeling and analyzing human behaviors using computational techniques (b) Designing and conducting cognitive experiments using robots and various technologies ?Presentation: Students will give a 15-20 min presentation about their hands-on projects. ?Final report: Students will submit a 5-6 page final report summarizing the lectures and hands-on projects. |
| 13 | Required readings | ?Yukie Nagai, “Predictive learning: its key role in early cognitive development,” Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1771):20180030, 2019. ?Karl Friston, Rosalyn J. Moran, Yukie Nagai, Tadahiro Taniguchi, Hiroaki Gomi, and Josh Tenenbaum, “World model learning and inference,” Neural Networks, 144:573-590, 2021. ?Yukie Nagai, “Social Cognition,” Cognitive Robotics, A. Cangelosi and M. Asada (Eds.), The MIT Press, 2022. |
| 14 | Reference readings | ?Angelo Cangelosi and Matthew Schlesinger, “Developmental Robotics,” The MIT Press, 2015. ?Jun Tani, “Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena,” Oxford University Press, 2016. ?Angelo Cangelosi and Minoru Asada (Eds), “Cognitive Robotics,” The MIT Press, 2022. |
| 15 | Notes on Taking the Course | - |
´ºÓêÖ±²¥app Global Unit Courses (GUC)
International Education Promotion Group, Education and Student Support Department
´ºÓêÖ±²¥app, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8652 JAPAN
For inquiries regarding GUC, kindly direct them to the following email address:
utokyo-guc.adm(at)gs.mail.u-tokyo.ac.jp *Please change (at) to @
International Education Promotion Group, Education and Student Support Department
´ºÓêÖ±²¥app, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8652 JAPAN
For inquiries regarding GUC, kindly direct them to the following email address:
utokyo-guc.adm(at)gs.mail.u-tokyo.ac.jp *Please change (at) to @
