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  Learning the systematic transformation of holographic reduced representations

Neumann, J. (2002). Learning the systematic transformation of holographic reduced representations. COGNITIVE SYSTEMS RESEARCH, 3(2), 227-235. doi:10.1016/S1389-0417(01)00059-6.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-C32A-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-187B-6
Genre: Journal Article

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 Creators:
Neumann, Jane1, Author              
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1External Organizations, ou_persistent22              

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Free keywords: Holographic reduced representation; Holistic processing; Systematicity; Connectionist representation of hierarchical structures; Connectionist symbol processing
 Abstract: Holographic Reduced Representation is a representational scheme which allows for the representation of variable-sized structures in a distributed manner. It has been shown that these compositional structures can be transformed holistically. However, in order to do so, the transformation vector was constructed by hand. In this paper we present two methods of learning the holistic transformation of Holographic Reduced Representations from examples. We show that the acquired knowledge can be generalised to structures containing unseen elements and to structures more complex than the training examples. These generalisations require a degree of systematicity which to our knowledge has not yet been achieved by other comparable methods.

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Language(s): eng - English
 Dates: 2002
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 394228
DOI: 10.1016/S1389-0417(01)00059-6
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Title: COGNITIVE SYSTEMS RESEARCH
  Other : Cogn. Syst. Res.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Amsterdam? : Elsevier
Pages: - Volume / Issue: 3 (2) Sequence Number: - Start / End Page: 227 - 235 Identifier: ISSN: 1389-0417
CoNE: https://pure.mpg.de/cone/journals/resource/110978984448179