590NC Presentation List

Week Topic Paper Number(s) Presenter
Oct. 1 Introduction and organizational discussion None Raj
Oct. 8 Introduction to motor learning 18 David Grimes
Oct. 15 Introduction to forward and inverse models 11 Aaron Shon
Oct. 22 Computational approaches to motor control 17 Jeremy Holleman
Oct. 29 Robotic Imitation Learning 1 David Hsu
Nov. 5 Learning Motor Skills by Imitation 2 Doug Downey
Nov. 12 Invited Lecture: Imitation Learning in Infants 13 Andy Meltzoff (CMBL)
Nov. 19 Architectures for learning internal models 8 Chris Baker
Nov. 26 Biomechanical Dynamics 15,16 Josh Tasman
Dec. 3 Evidence for Internal Models 19 Seth Bridges
Dec. 10 No Class due to NIPS conference - -

Location: We meet in Mary Gates 278 every Tuesday from 1:30 to 2:50 PM.

Tentative list of papers (alphabetically by first author):

  1. Learning of Oculo-Motor Control: a Prelude to Robotic Imitation. L. Berthouze, P. Bakker and Y. Kuniyoshi. In Proc. IEEE/RSJ IROS'96, volume 1, pages 376-381, 1996.
  2. Learning motor skills by imitation: a biologically inspired robotic model. A. Billard. Cybern. and Systems 32:155-193, 2001.
  3. Predicting the consequences of our own actions: the role of sensorimotor context estimation. S.J. Blakemore, S.J. Goodbody, and D.M. Wolpert. J. Neurosci. 18(18): 7511-7518, 1998.
  4. On the recognition of abstract Markov policies. H.H. Bui, S. Venkatesh, and G. West. Seventeenth National Conference on Artificial Intelligence (AAAI-2000). Austin, Texas, August 2000
  5. Imitation as a dual-route process featuring predictive and learning components: a biologically-plausible computational model. Y. Demiris and G. Hayes. Chapter 13 in Imitation in Animals and Artifacts, K. Dautenhahn and C. Nehaniv (eds.), MIT Press, 2002 (in press).
  6. Perceptuo-Motor Primitives in Imitation. J. Demiris and M.J. Mataric. In Working Notes, Agents '98, 1998.
  7. Modular decomposition in visuomotor learning. Z. Ghahramani and D.M. Wolpert. Nature 386:392-395, 1997.
  8. MOSAIC Model for Sensorimotor Learning and Control. M. Haruno, D.M. Wolpert, and M. Kawato. Neural Comp. 13, 2201-2220, 2001.
  9. Computational aspects of motor control and motor learning. M.I. Jordan. In H. Heuer and S. Keele (eds.), Handbook of Perception and Action: Motor Skills. New York: Academic Press, 1996.
  10. Modular and hierarchical learning systems. M.I. Jordan and R.A. Jacobs. In M. Arbib (ed.), The Handbook of Brain Theory and Neural Networks. Cambridge, MA: MIT Press, 1995.
  11. Forward models: Supervised learning with a distal teacher. M.I. Jordan and D.E. Rumelhart. Cognitive Science 16, 307-354, 1992.
  12. Internal models for motor control and trajectory planning. M. Kawato. Current Opinions in Neurobiology 9:718-727, 1999.
  13. Born to Learn: What Infants Learn from Watching Us. A.N. Meltzoff. In N. Fox and J.G. Worhol (eds.), The Role of Early Experience in Infant Development. Skillman , NJ: Pediatric Inst. Publications, 1999.
  14. Forward models for physiological motor control. R.C. Miall and D.M. Wolpert. Neural Networks 9(8):1265-1279, 1996.
  15. Intermediate motor learning as decreasing active (dynamical) degrees of freedom. S. Mitra, P.G. Amazeen, and M.T. Turvey. Human Movement Science 17: 17-65, 1998.
  16. Dynamics of effortful touch and interlimb coordination. M.T. Turvey. J. Biomechanics 31: 873-882, 1998.
  17. Computational approaches to motor control. D.M. Wolpert. Trends in Cog. Sci. 1(6):209-216, 1997.
  18. Perspectives and problems in motor learning. D.M. Wolpert, Z. Ghahramani, and J.R. Flanagan. Trends Cog. Sci. 5(11):487-494, 2001.
  19. An internal model for sensorimotor integration. D.M. Wolpert, Z. Ghahramani and M.I. Jordan. Science 269:1880-1882.
Head back to the 590NC course web page
Comments to: Raj Rao or Aaron Shon