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Neuro-symbolic Representation of Logic Programs Defining Infinite Sets

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Book cover Artificial Neural Networks – ICANN 2010 (ICANN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6352))

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Abstract

It has been one of the great challenges of neuro-symbolic integration to represent recursive logic programs using neural networks of finite size. In this paper, we propose to implement neural networks that can process recursive programs viewed as inductive definitions.

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Author information

Authors and Affiliations

  1. School of Computing, University of Dundee, UK

    Ekaterina Komendantskaya

  2. Department of Computing, Imperial College, London, UK

    Krysia Broda

  3. Department of Computing, City University London, UK

    Artur d’Avila Garcez

Authors
  1. Ekaterina Komendantskaya
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  2. Krysia Broda
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  3. Artur d’Avila Garcez
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Editor information

Editors and Affiliations

  1. Department of Informatics, TEI of Thessaloniki, 57400, Sindos, Greece

    Konstantinos Diamantaras

  2. School of Physics, Astronomy, and Informatics, Department of Informatics, Nicolaus Copernicus University, ul. Grudziadzka 5, 87-100, Torun, Poland

    Wlodek Duch

  3. Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, Pantazidou 193, 68200, Orestiada, Thrace, Greece

    Lazaros S. Iliadis

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Komendantskaya, E., Broda, K., Garcez, A.d. (2010). Neuro-symbolic Representation of Logic Programs Defining Infinite Sets. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15819-3_39

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  • DOI: https://doi.org/10.1007/978-3-642-15819-3_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15818-6

  • Online ISBN: 978-3-642-15819-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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