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.
Cite
CITATION STYLE
Moga, S., & Gaussier, P. (1999). A neural structure for learning by imitation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1674, pp. 314–318). Springer Verlag. https://doi.org/10.1007/3-540-48304-7_40
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