1A2-O07 Acquiring the early communication based on the reward prediction model

This paper proposes a learning model which enables a baby robot to acquire the early communication in human development. The robot stores the time sequence of sensor information in its memory when the internal state rises up by the sudden sensor change such as big sound or face detection. The memory helps the robot to predict the response of the caregiver. The experimental result shows that the robot can acquire one of the early communications, peekaboo, by the proposed system.