Organisé par le LIASD.
One of the most significant challenges in robotics is to achieve closer interactions between humans and robots. Mutual behaviors occurring during interpersonal interaction provide unique insights into the complexities of the processes underlying human-robot coordination. In particular, interpersonal interaction, the process by which two or more people exchange information through verbal (what is said) and non-verbal (how it is said) messages could be exploited to both establish interaction and inform about the quality of interaction.
In this talk, we will report our recent works on social learning for (i) detecting individual traits such as pathology and identity during human-robot interaction, (ii) task learning from unlabeled teaching signals. We will also describe how these frameworks could be employed to investigate coordination mechanisms and in particular when it comes to pathologies such as autism spectrum disorders.
Jeudi 12 janvier 2017
De 13h30 à 15h
Université Paris 8
UFR MITSIC - salle A148
Professeur des universités
Université Pierre et Marie Curie