Abstract
The Kaspar robot has been used with great success to work
as an education and social mediator with children with autism spectrum
disorder. Enabling the robot to automatically generate causal explana-
tions is key to enrich the interaction scenarios for children and promote
trust in the robot. We present a theory of causal explanation to be em-
bedded in Kaspar. Based on this theory, we build a causal model and
an analysis method to calculate causal explanations. We implement our
method in Java with inputs provided by a human operator. This model
automatically generates the causal explanation that are then spoken by
Kaspar. We validate our explanations for user satisfaction in an empirical
evaluation.
as an education and social mediator with children with autism spectrum
disorder. Enabling the robot to automatically generate causal explana-
tions is key to enrich the interaction scenarios for children and promote
trust in the robot. We present a theory of causal explanation to be em-
bedded in Kaspar. Based on this theory, we build a causal model and
an analysis method to calculate causal explanations. We implement our
method in Java with inputs provided by a human operator. This model
automatically generates the causal explanation that are then spoken by
Kaspar. We validate our explanations for user satisfaction in an empirical
evaluation.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 14th International Conference on Social Robotics |
| Subtitle of host publication | ICSR 2022 |
| Publisher | Springer |
| Number of pages | 14 |
| Publication status | Published - Dec 2022 |