Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405626 | Neural Networks | 2009 | 10 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
A. Revel, P. Andry,