Hatice Köse

Pinar Uluer, Hatice Kose, Agnieszka Landowska et al.

The coronavirus disease (COVID-19) pandemic affected our lives deeply, just like everyone else, the children also suffered from the restrictions due to COVID-19 affecting their education and social interactions with others, being restricted from play areas and schools for a long time. Although social robots provide a promising solution to support children in their education, healthcare and social interaction with others, the precautions due to COVID-19 also introduced new constraints in the social robotics research. In this paper, we will discuss the benefits and challenges encountered in child-robot interaction due to COVID-19 based on two user studies. The first study involves children with hearing disabilities, and Pepper humanoid robot to support their audiometry tests. The second study includes the child-sized humanoid robot Kaspar and interaction games with children with autism spectrum disorder (ASD).

Frank Broz, Chrystopher L. Nehaniv, Hatice Kose-Bagci et al.

In this article, an enactive architecture is described that allows a humanoid robot to learn to compose simple actions into turn-taking behaviors while playing interaction games with a human partner. The robot's action choices are reinforced by social feedback from the human in the form of visual attention and measures of behavioral synchronization. We demonstrate that the system can acquire and switch between behaviors learned through interaction based on social feedback from the human partner. The role of reinforcement based on a short term memory of the interaction is experimentally investigated. Results indicate that feedback based only on the immediate state is insufficient to learn certain turn-taking behaviors. Therefore some history of the interaction must be considered in the acquisition of turn-taking, which can be efficiently handled through the use of short term memory.