Abstract
The problem of category learning has been traditionally investigated by employing disembodied categorization models. One of the basic tenets of embodied cognitive science states that categorization can be interpreted as a process of sensory-motor coordination, in which an embodied agent, while interacting with its environment, can structure its own input space for the purpose of learning about categories. Many researchers, including John Dewey and Jean Piaget, have argued that sensory-motor coordination is crucial for perception and for development. In this paper we give a quantitative account of why sensory-motor coordination is important for perception and category learning.
R.t.B and M.L: Work done at the Artificial Intelligence Laboratory in Zurich.
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© 2003 Springer-Verlag Berlin Heidelberg
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te Boekhorst, R., Lungarella, M., Pfeifer, R. (2003). Dimensionality Reduction through Sensory-Motor Coordination. In: Kaynak, O., Alpaydin, E., Oja, E., Xu, L. (eds) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. ICANN ICONIP 2003 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44989-2_59
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DOI: https://doi.org/10.1007/3-540-44989-2_59
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