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A model seeker: Extracting global constraint models from positive examples

  • Nicolas Beldiceanu
  • , Helmut Simonis
  • IMT Atlantique

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

We describe a system which generates finite domain constraint models from positive example solutions, for highly structured problems. The system is based on the global constraint catalog, providing the library of constraints that can be used in modeling, and the Constraint Seeker tool, which finds a ranked list of matching constraints given one or more sample call patterns. We have tested the modeler with 230 examples, ranging from 4 to 6,500 variables, using between 1 and 7,000 samples. These examples come from a variety of domains, including puzzles, sports-scheduling, packing & placement, and design theory. When comparing against manually specified "canonical" models for the examples, we achieve a hit rate of 50%, processing the complete benchmark set in less than one hour on a laptop. Surprisingly, in many cases the system finds usable candidate lists even when working with a single, positive example.

Original languageEnglish
Title of host publicationPrinciples and Practice of Constraint Programming - 18th International Conference, CP 2012, Proceedings
Pages141-157
Number of pages17
DOIs
Publication statusPublished - 2012
Event18th International Conference on Principles and Practice of Constraint Programming, CP 2012 - Quebec City, QC, Canada
Duration: 8 Oct 201212 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7514 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Principles and Practice of Constraint Programming, CP 2012
Country/TerritoryCanada
CityQuebec City, QC
Period8/10/1212/10/12

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