A Neural Structure for Learning by Imitation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1999

AUTHORS

Sorin Moga , Philippe Gaussier

ABSTRACT

In this paper, we present a neural architecture for a mobile robot in order to learn how to imitate a sequence of actions. We show that the use of a representation of the information in a continuous and dynamic way is necessary and the use of the neural fields can be a good solution to control the dynamic of several degrees of freedom with a single internal representation. More... »

PAGES

314-318

Book

TITLE

Advances in Artificial Life

ISBN

978-3-540-66452-9
978-3-540-48304-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-48304-7_40

DOI

http://dx.doi.org/10.1007/3-540-48304-7_40

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041140190


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