Existing robotics technology is still mostly limited to being used by expert programmers who can adapt the systems to new required conditions, but not flexible and adaptable by non-expert workers or end-users. Imitation Learning (IL) has obtained considerable attention as a potential direction for enabling all kinds of users to easily program the behavior of robots or virtual agents. Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of the robot’s behavior. In...