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Combination of Nonlinear Terms in Interval Constraint Satisfaction Techniques

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Artificial Intelligence and Symbolic Computation (AISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3249))

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Abstract

Nonlinear constraint systems can be solved by combining consistency techniques and search. In this approach, the search space is reduced using local reasoning on constraints. However, local computations may lead to slow convergences. In order to handle this problem, we introduce a symbolic technique to combine nonlinear constraints. Such redundant constraints are further simplified according to the precision of interval computations. As a consequence, constraint reasoning becomes tighter and the solving process faster. The efficiency of this approach is shown using experimental results from a prototype.

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Author information

Authors and Affiliations

  1. LINA, University of Nantes, 2, rue de la Houssinière, BP 92208, 44322, Nantes Cedex 3, France

    Laurent Granvilliers & Mina Ouabiba

Authors
  1. Laurent Granvilliers
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  2. Mina Ouabiba
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Editor information

Editors and Affiliations

  1. Research Institute for Symbolic Computation, Johannes Kepler University, Linz, Austria

    Bruno Buchberger

  2. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, UK

    John Campbell

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© 2004 Springer-Verlag Berlin Heidelberg

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Granvilliers, L., Ouabiba, M. (2004). Combination of Nonlinear Terms in Interval Constraint Satisfaction Techniques. In: Buchberger, B., Campbell, J. (eds) Artificial Intelligence and Symbolic Computation. AISC 2004. Lecture Notes in Computer Science(), vol 3249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30210-0_11

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  • DOI: https://doi.org/10.1007/978-3-540-30210-0_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23212-4

  • Online ISBN: 978-3-540-30210-0

  • eBook Packages: Springer Book Archive

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