http://cogprints.org/id/eprint/3343 2011-03-11T08:55:26Z info:eu-repo/semantics/descriptiveMetadata A Developmental Approach for low-level Imitations Andry, Pierre Gaussier, Philippe Nadel, Jacqueline Courant, Michele Machine Learning Neural Nets Robotics 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. Lund University Cognitive Studies Prince, Christopher G. Berthouze, Luc Kozima, Hideki Bullock, Daniel Stojanov, Georgi Balkenius, Christian 2003 Conference Poster PeerReviewed application/pdf http://cogprints.org/3343/1/Andry.pdf Andry, Pierre and Gaussier, Philippe and Nadel, Jacqueline and Courant, Michele (2003) A Developmental Approach for low-level Imitations. [Conference Poster] http://cogprints.org/3343/ info:eu-repo/semantics/objectFile info:eu-repo/semantics/humanStartPage