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nEUro-IT.net workshop

 The Brain Mechanisms of Imitation Learning

To be held at the occasion of the

Eighteenth Annual Conference on Neural Information Processing Systems

NIPS-2004

December 17, 2004, 7h30-19h00

Whistler, B.C, Canada

 
Overview  
   
 



Objectives  

Imitation learning is a powerful mechanism for dimensionality reduction. When observing either good or bad examples, one can improve its search for a possible solution, by either starting the search from the observed good solution (local optima), or conversely, by eliminating from the search space what is known as a bad solution. Imitation learning appears thus to be a powerful tool for learning in both animals and artifacts.

Imitation learning has for long been a key topic of Psychology and Robotics. Recent neurosciences evidence of specific brain pathways underlying primates’ imitation capability have set the ground for computational studies of these neural correlates. This workshop aims at assessing recent progresses in thus area. Because imitation learning has at core motor learning, the workshop will gather experts in both motor learning and imitation learning.  Key questions that will be discussed in the workshop include:

  • Can imitation use known motor learning techniques or does it require the development of new learning and control policies?
  • How does imitation contribute and complement motor learning?
  • Does imitation speed up skill learning?
  • What are the costs of imitation learning?
  • How could the metric of imitation learning drive the choice of learning technique?
  • How could we define a general metric of imitation performance?
  • What is the role of visual attention and gesture recognition in imitation? 
  • Do models of human kinematics, used in gesture recognition, drive the reproduction of the task?
  • Can one find a level of representation of movement common to both gesture recognition and motor control?

  • Program  (Tentative)
    TIME TITLE
    7:30 Welcome and overview,   Aude Billard & Stefan Schaal
    PART I:  Imitation  (Behavioral Studies)
    7:35-8:05 Andi Wohlschlager  - (Max Planck Institute, Munich
    The ideomotor principle in imitation and action perception
    8:05-8:25 Kai Engberg  - (Max Planck Institute, Munich)
    Am I Special? Linking Action Awareness and Functional Processing 
    8:25:-8:45 COFFEE BREAK
    PART II:  Imitation  (Brain Imaging and Neural Modeling)
    8:45-9:15 Thierry Chaminade - (ATR & Univ. Washington)
    Motor Resonance: A neurophysiologically plausible framework combining execution and perception of action.
    9:15-9:35 Eric Sauser - (EPFL)
    Neural model of the frame of reference transformations underlying goal-directed imitation
    PART 1I: Imitation Learning (Robotics) 
    9:35-10:05 Raj Rao - (Univ. Washington)    
    A Bayesian Model for Imitation
    10:05-10h:25 Anthony Dearden - (Imperial College London
    Developmental learning of predictive models for robotics
    10:30:-16:00 BREAK 
    16:00-16:30 Aude Billard  - (EPFL)
    Discovering Imitation Strategies through Categorization of Multi-Dimensional Data
    16:30-16:50 Francesco Orabona - (University of Genova)
    Object-based model of the visual attention for imitation
    16:50-17h:10 Michele Tagliabue - (Polytechnico di Milano
    A model of motor planning theory underlying human visuo-motor control
    17:10-17:30 Ken Prepin - (ENSEA & Hôpital de la Salpétrière, Paris)
    Imitation properties amplified by communication.
    17:30-17:45 COFFEE BREAK
    PART 1II:  Imitation Learning, Reinforcement Learning & Motor Learning
    17:45-18:15 Pieter Abbeel  - (Stanford Univ.)
    Apprenticeship Learning via Inverse Reinforcement Learning
    18:15-18:45 Stefan Schaal  - (USC )
    Imitation and Reinforcement Learning with Dynamic Motor Primitives
    18:45-19:00 

    Discussion & Wrap-up ----  Aude Billard & Stefan Schaal


    Organizers  

    Aude Billard   
    Autonomous Systems Lab
    EPFL - Swiss Federal Institute of Technology
    CH-1015 Lausanne, Switzerland
    tel:  +41 (21) 693.54.64
    fax: +41 (21) 693.78.06
    email: aude.billard@epfl.ch

    Stefan Schaal   
    CLMC Laboratory
    Cs Dept, University of Southern California
    90089-2520 Los Angeles, USA
    tel:  +1 (213) 740 9418
    fax: +1 (213) 740 1510
    email: sschaal@usc.edu


    Proceedings  

    You can download a pdf summary of all abstracts here

    The workshop will then lead to an open call for a special issue in one or two of the following journals (e.g. Neural Networks,  IEEE Trans. of NN, B&M, Neurocomputing)., to be published in late spring 2005.



    Last update: 24/08/06