A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot
Abolfazl Zaraki, Mehdi Khamassi, Luke Wood, Gabriella Lakatos, Costas S. Tzafestas, Farshid Amirabdollahian, Ben Robins, Kerstin Dautenhahn
- Year
- 2019
- Citations
- 18
- Access
- Open access
Abstract
Abstract This paper presents a contribution aiming at testing novel child–robot teaching schemes that could be used in future studies to support the development of social and collaborative skills of children with autism spectrum disorders (ASD). We present a novel experiment where the classical roles are reversed: in this scenario the children are the teachers providing positive or negative reinforcement to the Kaspar robot in order for it to learn arbitrary associations between different toy names and the locations where they are positioned. The objective is to stimulate interaction and collaboration between children while teaching the robot, and also provide them tangible examples to understand that sometimes learning requires several repetitions. To facilitate this game, we developed a reinforcement learning algorithm enabling Kaspar to verbally convey its level of uncertainty during the learning process, so as to better inform the children about the reasons behind its successes and failures. Overall, 30 typically developing (TD) children aged between 7 and 8 (19 girls, 11 boys) and 9 children with ASD performed 25 sessions (16 for TD; 9 for ASD) of the experiment in groups, and managed to teach Kaspar all associations in 2 to 7 trials. During the course of study Kaspar only made rare unexpected associations (2 perseverative errors and 2 win-shifts, within a total of 314 trials), primarily due to exploratory choices, and eventually reached minimal uncertainty. Thus, the robot’s behaviour was clear and consistent for the children, who all expressed enthusiasm in the experiment.
Keywords
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