Abstract
This chapter outlines how the derived Facetwise LCS approach can carry over to the design of cognitive learning systems. We propose the integration of LCS-like search mechanisms into cognitive structures for structural growth and distributed, modular relevancy identification. The mechanisms may be integrated into multi-layered, hierarchical learning structures and may influence solution growth interdependently using only RL mechanisms and evolutionary problem solution structuring.
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© 2006 Springer
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Butz, M.V. (2006). Towards Cognitive Learning Classifier Systems. In: Rule-Based Evolutionary Online Learning Systems. Studies in Fuzziness and Soft Computing, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31231-5_12
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DOI: https://doi.org/10.1007/3-540-31231-5_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25379-2
Online ISBN: 978-3-540-31231-4
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