Creating hierarchical categories using cell assemblies

Article

Huyck, C. 2007. Creating hierarchical categories using cell assemblies. Connection Science. 19 (1), pp. 1-24. https://doi.org/10.1080/09540090600779713
TypeArticle
TitleCreating hierarchical categories using cell assemblies
AuthorsHuyck, C.
Abstract

This paper shows how the CA concept can be used to learn hierarchical categories. Elements of basic categories are presented to the system. It learns those categories, but also learns higher order categories. This system can use these categories for default reasoning. This is novel because it is all done with biologically plausible fatiguing Leaky Integrate and Fire neurons. It makes use of compensatory learning work to form CAs. This also shows neural support for the well worn psychological work in categorisation. This work is being used in a current EPSRC grant to provide semantic relatedness and reduce network size.

Keywordscell assembly; attractor net; Hebbian learning; hierarchical categorization
Research GroupArtificial Intelligence group
PublisherTaylor and Francis
JournalConnection Science
ISSN0954-0091
Electronic1360-0494
Publication dates
Online16 Mar 2007
PrintMar 2007
Publication process dates
Deposited17 Oct 2008
Submitted08 Mar 2006
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1080/09540090600779713
Web of Science identifierWOS:000245629300001
LanguageEnglish
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