Linking neural and symbolic representation and processing of conceptual structures

Frank van der Velde*, Jamie Forth, Deniece S. Nazareth, Geraint A. Wiggins

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
87 Downloads (Pure)

Abstract

We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.

Original languageEnglish
Article number1297
Number of pages16
JournalFrontiers in psychology
Volume8
DOIs
Publication statusPublished - 10 Aug 2017

Keywords

  • Cognitive architecture
  • Compositional learning
  • Hebbian learning
  • In situ representations
  • Incremental learning
  • Memory representation

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