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The Adaptive Constraint Engine

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Principles and Practice of Constraint Programming - CP 2002 (CP 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2470))

Abstract

The Adaptive Constraint Engine (ACE) seeks to automate the application of constraint programming expertise and the extraction of domain-specific expertise. Under the aegis of FORR, an architecture for learning and problem-solving, ACE learns search-order heuristics from problem solving experience. This paper describes ACE’s approach, as well as new experimental results on specific problem classes. ACE is both a test-bed for CSP research and a discovery environment for new algorithms.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Hunter College and The Graduate School of The City University of New York, New York, NY, 10021, USA

    Susan L. Epstein, Anton Morozov & Bruce Samuels

  2. Cork Constraint Computation Centre, University College Cork, Cork, Ireland

    Eugene C. Freuder & Richard Wallace

Authors
  1. Susan L. Epstein
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  2. Eugene C. Freuder
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  3. Richard Wallace
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  4. Anton Morozov
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  5. Bruce Samuels
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Editor information

Editors and Affiliations

  1. Brown University, Box 1910, Providence, RI, 02912, USA

    Pascal Van Hentenryck

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© 2002 Springer-Verlag Berlin Heidelberg

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Epstein, S.L., Freuder, E.C., Wallace, R., Morozov, A., Samuels, B. (2002). The Adaptive Constraint Engine. In: Van Hentenryck, P. (eds) Principles and Practice of Constraint Programming - CP 2002. CP 2002. Lecture Notes in Computer Science, vol 2470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46135-3_35

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  • DOI: https://doi.org/10.1007/3-540-46135-3_35

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44120-5

  • Online ISBN: 978-3-540-46135-7

  • eBook Packages: Springer Book Archive

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