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GWAI-91 15. Fachtagung für Künstliche Intelligenz pp 244–253Cite as

Transforming Constraint Relaxation Networks into Boltzmann Machines

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Part of the book series: Informatik-Fachberichte ((2252,volume 285))

Abstract

We describe how to transform constraint networks—which may involve a particular form of constraint relaxation—into corresponding Boltzmann machines, thereby viewing constraint satisfaction as a problem of combinatorial optimization. We discuss feasibility and order preservingness of the consensus function used and give a necessary and sufficient condition for a locally optimal configuration to correspond to a solution of the constraint network.

This work is partially funded by the German Federal Ministry for Research and Technology (BMFT) in the joint project TASSO under grant ITW8900A7. TASSO is also part of the GMD Leitvorhaben Assisting Computer (AC). Thanks to our colleagues Christoph Lischka and Gerd PaaB for comments on a draft of this paper.

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Author information

Authors and Affiliations

  1. German National Research Center for Computer Science (GMD), Schloß Birlinghoven, D-5205, Sankt Augustin 1, Germany

    Joachim Hertzberg & Hans Werner Guesgen

Authors
  1. Joachim Hertzberg
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  2. Hans Werner Guesgen
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Editor information

Editors and Affiliations

  1. Institut für Angewandte Informationstechnik, Forschungsbereich KI, Gesellschaft für Mathematik und Datenverarbeitung (GMD), Schloß Birlinghoven, W-5205, Sankt Augustin 1, Deutschland

    Thomas Christaller

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© 1991 Springer-Verlag Berlin Heidelberg

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Hertzberg, J., Guesgen, H.W. (1991). Transforming Constraint Relaxation Networks into Boltzmann Machines. In: Christaller, T. (eds) GWAI-91 15. Fachtagung für Künstliche Intelligenz. Informatik-Fachberichte, vol 285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-02711-0_27

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  • DOI: https://doi.org/10.1007/978-3-662-02711-0_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54558-3

  • Online ISBN: 978-3-662-02711-0

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