Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
This paper discusses associative learning of a partner robots
through interaction with people. Human interaction based on
gestures is very important to realize the natural
communication. The meaning of gestures can be understood
through the actual interaction with a human and the
imitation of a human. Therefore, we propose a method for
associative learning based on imitation and conversation to
realize the natural communication. Steady-state genetic
algorithms are applied for detecting human face and objects
in image processing. Spiking neural networks are applied for
memorizing spatio-temporal patterns of human hand
motions, and relationship among perceptual information.
Furthermore, we conduct several experiments of the partner
robot on the interaction based on imitation and conversation
with people. The experimental results show that the
proposed method can refine the relationship among the
perceptual information, and can reflect the updated
relationship to the natural communication with a human.
