Teaching and learning using semantic labels

Abstract

We improve robotic learning from demonstration (LfD) via an active learning process of interacting with a human expert to establish a semantic structure and labels for a sign language task. This process situates a learned task in a human-accessible conceptual framework, in order to improve skill transfer not only from expert human teacher to robot, but from robot to novice human learner.