Biography
Yukie Nagai received the Ph.D. in Engineering from Osaka University in 2004. She was a Post-Doctoral Researcher with the National Institute of Information and Communications Technology (NICT) from 2004 to 2006, and Bielefeld University from 2006 to 2009. She then became a Specially Appointed Associate Professor with Osaka University in 2009 and a Senior Researcher with NICT in 2017. Since April 2019, she is a Project Professor with the University of Tokyo.
Dr. Nagai has been investigating underlying neural mechanisms for social cognitive development by means of computational approach. She designs neural network models for robots to learn to acquire cognitive functions based on her theory of predictive learning. The simulator reproducing atypical perception in autism spectrum disorder (ASD) greatly impacts on the society as it enables people with and without ASD to better understand potential causes for social difficulties.
Abstract
Predictive Learning as a Computational Principle for Early Cognitive Development
My talk presents computational models for robots to acquire cognitive abilities as human infants do. A theoretical framework called predictive coding suggests that the human brain works as a predictive machine, that is, it tries to minimize prediction error, which is calculated as a difference between bottom-up sensory signals and top-down prediction. I have extended this theory and proposed predictive learning as a computational principle for early cognitive development. My talk shows how neural networks based on predictive learning enable robots to learn to generate own actions, estimate the goal of others’ actions, imitate them, and help others. I also discuss how the theory helps understand potential causes of autism spectrum disorder.
