Neurons or Symbols: Why does OR Remain Exclusive?

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1 Citation (Scopus)


Neuro-Symbolic Integration is an interdisciplinary area that endeavours to unify neural networks and symbolic logic. The goal is to create a system that combines the advantages of neural networks (adaptive behaviour, robustness, tolerance of noise and probability) and symbolic logic (validity of computations, generality, higher-order reasoning). Several different approaches have been proposed in the past. However, the existing neuro-symbolic networks provide only a limited coverage of the techniques used in computational logic. In this paper, we outline the areas of neuro-symbolism where computational logic has been implemented so far, and analyse the problematic areas. We show why certain concepts cannot be implemented using the existing neuro-symbolic networks, and propose four main improvements needed to build neuro-symbolic networks of the future.

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
Number of pages6
ISBN (Print)9789896740146
Publication statusPublished - 2009
EventInternational Joint Conference on Computational Intelligence 2009 - Funchal, Portugal
Duration: 5 Oct 20097 Oct 2009


ConferenceInternational Joint Conference on Computational Intelligence 2009
Abbreviated titleIJCCI 2009


  • Computational Logic in Neural Networks
  • Neuro-Symbolic Networks
  • Connectionism
  • Hybrid networks


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