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A symbolic approach to interval constraint problems

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Artificial Intelligence and Symbolic Mathematical Computing (AISMC 1992)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 737))

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Abstract

We report on a symbolic approach to solving constraint problems, which uses relation algebra. The method gives good results for problems with constraints that are relations on intervals. Problems of up to 500 variables may be solved in expected cubic time. Strong evidence is presented that significant backtracking on random problems occurs only in the range 6 ≤ n.c ≤ 15, for c ≥ 0.5, where n is the number of variables, and c is the ratio of non-trivial constraints to possible constraints in the problem. Space performance of the method is affected by the branching factor during search, and time performance by path-consistency calculations, including the calculation of compositions of relations.

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Author information

Author notes

  1. Peter Ladkin

    Present address: Dept. of Computing Science, University of Stirling, FK9 4LA, Stirling, Scotland

Authors and Affiliations

  1. Universität Bern, Länggassstrasse 51, CH-3012, Bern

    Peter Ladkin

  2. Paderborn Center for Parallel Computing, Warburger Str. 100, D-4790, Paderborn, Germany

    Alexander Reinefeld

Authors
  1. Peter Ladkin
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  2. Alexander Reinefeld
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Corresponding author

Correspondence to Peter Ladkin .

Editor information

Jacques Calmet John A. Campbell

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© 1993 Springer-Verlag Berlin Heidelberg

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Ladkin, P., Reinefeld, A. (1993). A symbolic approach to interval constraint problems. In: Calmet, J., Campbell, J.A. (eds) Artificial Intelligence and Symbolic Mathematical Computing. AISMC 1992. Lecture Notes in Computer Science, vol 737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57322-4_4

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  • DOI: https://doi.org/10.1007/3-540-57322-4_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57322-7

  • Online ISBN: 978-3-540-48063-1

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