License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2022.15
URN: urn:nbn:de:0030-drops-166449
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16644/
Go to the corresponding LIPIcs Volume Portal

Coulombe, Christopher ; Quimper, Claude-Guy

Constraint Acquisition Based on Solution Counting

pdf-format:
LIPIcs-CP-2022-15.pdf (1 MB)

Abstract

We propose CABSC, a system that performs Constraint Acquisition Based on Solution Counting. In order to learn a Constraint Satisfaction Problem (CSP), the user provides positive examples and a Meta-CSP, i.e. a model of a combinatorial problem whose solution is a CSP. This Meta-CSP allows listing the potential constraints that can be part of the CSP the user wants to learn. It also allows stating the parameters of the constraints, such as the coefficients of a linear equation, and imposing constraints over these parameters. The CABSC reads the Meta-CSP using an augmented version of the language MiniZinc and returns the CSP that accepts the fewest solutions among the CSPs accepting all positive examples. This is done using a branch and bound where the bounding mechanism makes use of a model counter. Experiments show that CABSC is successful at learning constraints and their parameters from positive examples.

BibTeX - Entry

@InProceedings{coulombe_et_al:LIPIcs.CP.2022.15,
  author =	{Coulombe, Christopher and Quimper, Claude-Guy},
  title =	{{Constraint Acquisition Based on Solution Counting}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{15:1--15:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16644},
  URN =		{urn:nbn:de:0030-drops-166449},
  doi =		{10.4230/LIPIcs.CP.2022.15},
  annote =	{Keywords: Constraint acquisition, CSP, Model counting, Solution counting}
}

Keywords: Constraint acquisition, CSP, Model counting, Solution counting
Collection: 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)
Issue Date: 2022
Date of publication: 23.07.2022

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI