Emergence of structured interactions: from a theoretical model to pragmatic robotics

Abstract

In this article, we present two neural architectures for the control of socially interacting robots. Beginning with a theoretical model of interaction inspired by developmental psychology, biology and physics, we present two sub-cases of the model that can be interpreted as "turn-taking" and "synchrony" at the behavioral level. These neural architectures are both detailed and tested in simulation. A robotic experiment is even presented for the "turn-taking" case. We then discuss the interest of such behaviors for the development of further social abilities in robots.