Parallel Rewriting in Neural Networks

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given first-order term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox.

Original languageEnglish
Title of host publicationIJCCI 2009 - Proceedings of the International Joint Conference on Computational Intelligence, Funchal, Madeira, Portugal, October 5-7, 2009
EditorsAntónio Dourado Correia, Agostinho C. Rosa, Kurosh Madani
PublisherINSTICC Press
Pages452-458
Number of pages7
ISBN (Print)9789896740146
Publication statusPublished - 2009
EventInternational Joint Conference on Computational Intelligence 2009 - Funchal, Portugal
Duration: 5 Oct 20097 Oct 2009

Conference

ConferenceInternational Joint Conference on Computational Intelligence 2009
Abbreviated titleIJCCI 2009
Country/TerritoryPortugal
CityFunchal
Period5/10/097/10/09

Keywords

  • Computational Logic in Neural Networks
  • Neuro-Symbolic Networks
  • Abstract Rewriting
  • Parallel Term-Rewriting
  • Unsupervised Learning
  • Computer Simulation of Neural Networks

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