This research project was partially funded by ERC Starting Grant EXPLORERS 240007.
Fifth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, vol. 123. Lund University Cognitive Studies, 2005, pp. 47–53.
 S. Calinon, F. Guenter, and A. Billard, “On learning, representing, and generalizing a task in a humanoid robot.” IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society, vol. 37, no. 2, pp. 286–98, Apr. 2007.
 D. H. Grollman and O. C. Jenkins, “Incremental Learning of Subtasks from Unsegmented Demonstration,” in IROS, Taipei, Taiwan, 2010.  S. Calinon and A. G. Billard, “Statistical Learning by Imitation of Com-
peting Constraints in Joint Space and Task Space,” Advanced Robotics,
vol. 23, pp. 2059–2076, 2009.  Y. Li, C. Fermuller, Y. Aloimonos, and H. Ji, “Learning shift-invariant
sparse representation of actions,” in 2010 IEEE Computer Society Con- ference on Computer Vision and Pattern Recognition. San-Francisco: IEEE, Jun. 2010, pp. 2630–2637.
 M. Pardowitz, S. Knoop, R. Dillmann, and R. D. Zo ̈llner, “Incremental learning of tasks from user demonstrations, past experiences, and vocal comments.” IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society, vol. 37, no. 2, pp. 322–32, Apr. 2007.
 R. S. Sutton, D. Precup, and S. Singh, “Between MDPs and semi- MDPs: A framework for temporal abstraction in reinforcement learning,” Artificial intelligence, vol. 112, no. 1, pp. 181–211, 1999.
 D.D.LeeandH.S.Seung,“Learningthepartsofobjectsbynon-negative matrix factorization.” Nature, vol. 401, no. 6755, pp. 788–91, Oct. 1999