A Neural Structure for Learning by Imitation

Authors:
Sorin Moga;Philippe Gaussier
Affiliations:
-;-
Venue:
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Year:
1999

Citing 1
Cited 1

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Proceedings of the 7th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface

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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.