http://cogprints.org/3343/
A Developmental Approach for low-level Imitations
Historically, a lot of authors in psychology and in
robotics tend to separate "true imitation" and its
related high-level mechanisms which seem to be exclusive to human adult, from low-level imitations or
"mimicries" observed on babies or primates. Closely,
classical researches suppose that an imitative artificial system must be able to build a model of
the demonstrator's geometry, in order to reproduce finely the movements on each joints. Conversely, we
will advocate that if imitation is viewed as a part of a
developmental course, then (1) an artificial developing system does not need to build any internal model
of the other, to perform real-time and low-level imitations of human movements despite the related correspondence problem between man and robot and,
(2) a simple sensory-motor loop could be at the basis
of multiples heterogeneous imitative behaviors often
explained in the literature by different models.
Andry, Pierre
Gaussier, Philippe
Nadel, Jacqueline
Courant, Michele
Machine Learning
Neural Nets
Robotics
Pierre
Andry
Philippe
Gaussier
Jacqueline
Nadel
Michele
Courant