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Predicting Numbers: An AI Approach to Solving Number Series

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Book cover KI 2011: Advances in Artificial Intelligence (KI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7006))

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Abstract

Solving number series poses a challenging problem for humans and Artificial Intelligence Systems. The task is to correctly predict the next number in a given series, in accordance with a pattern inherent to that series. We propose a novel method based on Artificial Neural Networks with a dynamic learning approach to solve number series problems. Our method is evaluated on an own experiment and over 50.000 number series from the Online Encyclopedia of Integer Sequences (OEIS) database.

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References

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Author information

Authors and Affiliations

  1. Center for Cognitive Science, Friedrichstr. 50, 79098, Freiburg, Germany

    Marco Ragni & Andreas Klein

Authors
  1. Marco Ragni
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  2. Andreas Klein
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Editor information

Editors and Affiliations

  1. Berlin School of Mind and Brain, Humboldt-University of Berlin, Unter den Linden 6, 10099, Berlin, Germany

    Joscha Bach

  2. TZI-Technologie-Zentrum Informatik und Informationstechnik, University of Bremen, Postfach 33 04 40, 28334, Bremen, Germany

    Stefan Edelkamp

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© 2011 Springer-Verlag Berlin Heidelberg

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Ragni, M., Klein, A. (2011). Predicting Numbers: An AI Approach to Solving Number Series. In: Bach, J., Edelkamp, S. (eds) KI 2011: Advances in Artificial Intelligence. KI 2011. Lecture Notes in Computer Science(), vol 7006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24455-1_24

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  • DOI: https://doi.org/10.1007/978-3-642-24455-1_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24454-4

  • Online ISBN: 978-3-642-24455-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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