Abstract
This article presents results of experiments in autonomous competence acquisition in mobile robots, in which associations between incoming sensor signals and corresponding motor responses are stored in an artificial neural network. The learning process is either autonomous (i.e., self-supervised), or supervised by a human operator and, due to the type of network used, fast.
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Nehmzow, U. (2000). Self-Supervised and Supervised Acquisition of Smooth Sensory-Motor Competences in Mobile Robots. In: Cruse, H., Dean, J., Ritter, H. (eds) Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3. Studies in Cognitive Systems, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0870-9_58
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DOI: https://doi.org/10.1007/978-94-010-0870-9_58
Publisher Name: Springer, Dordrecht
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