Learning from Demonstration is an important technology for the new wave of robots that are envisioned to work side-by-side with workers in factories as well as social robots. Most available techniques for learning from demonstration rely on the existence of a training set of demonstrations that is assumed to be pre-segmented and is usually processed in batch. Another problem with most available methods is the need to set the model complexity used to model the motion. In this paper, we propose a solution to both pr…