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Adaptive Constraint Satisfaction: The Quickest First Principle

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Computational Intelligence

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 1))

Abstract

The choice of a particular algorithm for solving a given class of constraint satisfaction problems is often confused by exceptional behaviour of algorithms. One method of reducing the impact of this exceptional behaviour is to adopt an adaptive philosophy to constraint satisfaction problem solving. In this report we describe one such adaptive algorithm, based on the principle of chaining. It is designed to avoid the phenomenon of exceptionally hard problem instances. Our algorithm shows how the speed of more naïve algorithms can be utilised safe in the knowledge that the exceptional behaviour can be bounded. Our work clearly demonstrates the potential benefits of the adaptive approach and opens a new front of research for the constraint satisfaction community.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom

    James E. Borrett & Edward P. K. Tsang

Authors
  1. James E. Borrett
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  2. Edward P. K. Tsang
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Editor information

Editors and Affiliations

  1. School of Computer Science, Cardiff University , 5 The Parade,Roath, CF24 3AA, Cardiff, UK

    Christine L. Mumford

  2. University of South Australia Adelaide , Mawson Lakes Campus, South Australia, Australia

    Lakhmi C. Jain

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Borrett, J.E., Tsang, E.P.K. (2009). Adaptive Constraint Satisfaction: The Quickest First Principle. In: Mumford, C.L., Jain, L.C. (eds) Computational Intelligence. Intelligent Systems Reference Library, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01799-5_7

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  • DOI: https://doi.org/10.1007/978-3-642-01799-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01798-8

  • Online ISBN: 978-3-642-01799-5

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