Neurons or symbols: why does OR remain exclusive?

Ekaterina Komendantskaya

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    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
    EditorsA Dourado, A Rosa, K Madani
    Place of PublicationSetubal
    PublisherInstitute for Systems and Technologies of Information, Control and Communication
    Number of pages6
    ISBN (Print)9789896740146
    Publication statusPublished - 2009
    Event1st International Joint Conference on Computational Intelligence - Funchal, Portugal
    Duration: 5 Oct 20097 Oct 2009


    Conference1st International Joint Conference on Computational Intelligence
    Abbreviated titleIJCCI 2009


    • Computational logic in neural networks
    • Neuro-symbolic networks
    • Connectionism
    • Hybrid networks
    • NETS


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