Learning robot-environment interaction with echo state networks (ESNs) is presented in this paper. ESNs are asked to bootstrap a robot's control policy from human teacher's demonstrations on the robot learner, and to generalize beyond the demonstration dataset. Benefits and problems involved in some navigation tasks are discussed, supported by real-world experiments with a small mobile robot. © 2010 Springer-Verlag.
CITATION STYLE
Oubbati, M., Kord, B., & Palm, G. (2010). Learning robot-environment interaction using echo state networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6226 LNAI, pp. 501–510). https://doi.org/10.1007/978-3-642-15193-4_47
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