Prospective Students

AI for Understanding Human Intelligence

About the lecturer

Yukie Nagai is a Project Professor at the International Research Center for Neurointelligence, the University of Tokyo. She received her Ph.D. in Engineering from Osaka University in 2004 and then worked at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she has been leading Cognitive Developmental Robotics Lab at the University of Tokyo. Her research interests include cognitive developmental robotics, computational neuroscience, and assistive technologies for developmental disorders. She has been investigating underlying neural mechanisms for social cognitive development by means of computational approaches. She was selected  as one of "30 women in robotics you need to know about" in 2019, "World’s 50 Most Renowned Women in Robotics" in 2020, and "35 Women in Robotics Engineering and Science" in 2022.
Prof. Yukie Nagai

Syllabus

1 Subject AI for Understanding Human Intelligence
2 Field Computer science, robotics
3 Key words Cognitive developmental robotics, neural network, predictive coding, neurodiversity, virtual reality
4 Global Unit 1
5 Lecturer Yukie Nagai
6 Period June 19 - 30, 2023
7 Time 1:00-2:30pm [June 19-23]
1:00-6:30pm [June 26-30]
(Japan Standard Time)
8 Lecture style In-person
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 Attendance and participation: 30%
Presentation: 30%
Final report: 40%
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 how to use artificial neural networks to investigate human intelligence
  • learned cognitive and neuroscience theories about human intelligence
  • acquired skills to program/run artificial neural networks
  • acquired skills to design and conduct robot/VR (virtual reality) experiments
  • acquired skills to computationally analyze behavioral and physiological data

Description
Human infants acquire various cognitive abilities in the first few years of life. Although the developmental dynamics of their behaviors have been closely analyzed, what neural, bodily, and social mechanisms guide the development remain a mystery.
In this course, I will introduce AI and robotics approaches to understanding the underlying mechanisms for infant development. The approach called cognitive developmental robotics aims to elucidate the principle of human intelligence by designing artificial systems that learn and develop like infants. In contrast to the analytical approach in neuroscience, cognitive science, and psychology, this constructive approach has the potential to uncover a unified principle of intelligence. 
The course consists of three parts: lecture, hands-on , and presentation. In the first week (Sessions 1-5), I will give lectures on how AI and robotics technologies can be used for investigating cognitive development. Computational studies using neural networks and humanoid robots will be introduced to explain how neural, bodily, and social mechanisms interact to guide cognitive development. In the second week (Sessions 6-17), students will work on hands-on projects  to learn practical challenges in pursuing the above studies. Students divided into groups will address one of the following topics: (a) programming of neural networks to test a computational theory of cognitive development, and (b) robot/VR experiments to examine neurodiversity in cognitive development. At the end of the second week (Sessions 18-20), students will give a presentation about their hands-on projects. Students will discuss how the theories of cognitive development can be tested using neural networks and/or a robot/VR and what they have achieved and learned from their projects.
 
Schedule
  • Sessions 1-5: Lecture
  1. Introduction to cognitive developmental robotics
  2. Sensorimotor development
  3. Social development
  4. Neurodiversity in development
  5. Roles of embodied social interaction
  • Sessions 6-17: Hands-on
  1. Programming of neural networks to test a computational theory of cognitive developmental
  2. Robot/VR experiments to examine neurodiversity in cognitive development
  • Sessions 18-20: Presentation

Assignments
  • Hands-on: Students divided into groups will address one of the following projects:
  1. Programming of neural networks to test a computational theory of cognitive developmental
  2. Robot/VR experiments to examine neurodiversity in cognitive development
  • Presentation: Students will give a 10-20 min presentation about their hands-on project.
  • Final report: Students will submit a 5-6 page final report summarizing the lecture and hands-on project.
13 Required readings Will be provided through the UTeLF in advance.
14 Reference readings Will be provided through the UTeLF in advance.
15 Notes on Taking the Course N/A

Contact

UTokyo Global Unit Courses
International Exchange Group, Education and Student Support Department,
The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8652 JAPAN

Please send all inquiries regarding the courses to the following email address:

utokyo-guc.adm(at)gs.mail.u-tokyo.ac.jp *Please change (at) to @
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