Imitation as a communication tool for online facial expression learning and recognition

We are interested in understanding how babies learn to recognize facial expressions without having a teaching signal allowing to associate a facial expression to a given abstract label (i.e the name of the facial expression `sadness´, `happiness´...). Our starting point was a mathematical model showing that if the baby uses a sensory motor architecture for the recognition of the facial expression then the parents must imitate the baby facial expression to allow the on-line learning. In this paper, a first series of robotics experiments showing that a simple neural network model can control the robot head and learn on-line to recognize the facial expressions (the human partner imitates the robot prototypical facial expressions) is presented. We emphasize the importance of the emotions as a mechanism to ensure the dynamical coupling between individuals allowing to learn more complex tasks.