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Abstract: In this paper, we discuss the usefulness of topology preservation in an on-line learning neural control system. We discuss biological and information processing arguments. Then, we propose an experiment performed on a mobile robot that shows that with a Probabilistic Topological Map (PTM) much less information needs to be learned than using a Winner Take All. Keywords Neural Networks, Topology Preservation, Internal Representation, On-Line Learning 1. Introduction Self-organized feature... (Update)
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BibTeX entry: (Update)
S. Zrehen and Ph. Gaussier. Why topological maps are useful for learning in an autonomous agent. In Proceedings PerAc, Lausanne, September 1994. IEEE Press. http://citeseer.ist.psu.edu/zrehen94why.html More
@misc{ zrehen94why,
author = "S. Zrehen and P. Gaussier",
title = "Why topological maps are useful for learning in an autonomous agent",
text = "S. Zrehen and Ph. Gaussier. Why topological maps are useful for learning
in an autonomous agent. In Proceedings PerAc, Lausanne, September 1994.
IEEE Press.",
year = "1994",
url = "citeseer.ist.psu.edu/zrehen94why.html" }
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