Yukie Nagai, National Institute of Information and Communications Technology (NICT), Japan
Title: Development of social cognition in robots
Abstract : My talk presents computational models for robots to acquire social
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. My talk shows how neural
networks based on predictive coding enable robots to learn to generate own actions,
estimate the goal of others' actions, imitate them, and help others.
Bio: Dr. Yukie Nagai is a Senior Researcher, National Institute of Information and
Communications Technology. She 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 such as
self-other cognition, estimation of others' intention and emotion, altruism, and so
on 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. She is the research director of JST CREST Cognitive Mirroring
since December 2016.