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TitleAction understanding and imitation learning in a robot-human task
Author(s)Erlhagen, Wolfram
Mukovskiy, Albert
Bicho, E.
Panin, Giorgio
Kiss, Casba
Knoll, Alois
Van Schie, Hein
Bekkering, Harold
KeywordsImitation learning
Dynamic field model
Action understanding
Issue date2005
JournalLecture Notes in Computer Science
CitationDUCH, W. [et al.], ed. – “Artificial neural networks : formal models and their applications - ICANN 2005 : 15th International Conference, Warsaw, Poland, September 11-15, 2005 : proceedings”. Berlin [etc.] : Springer, cop. 2005. ISBN 3-540-28755-8. p. 261-268.
Abstract(s)We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is biologically inspired as it reflects recent experimental findings in action observation/execution studies. We test its functionality in variations of an imitation paradigm in which the artefact has to reproduce the observed or inferred end state of a grasping-placing sequence displayed by a human model.
TypeConference paper
AccessOpen access
Appears in Collections:Offmath - Comunicações

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