Tuning constrained objects

Ricardo Soto, Laurent Granvilliers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Constrained objects provide a suitable object-oriented style for modeling systems under constraints. A set of classes is defined to represent a problem, whose state is then controlled by a constraint satisfaction engine. This engine is commonly a black-box based on a predefined and non-customizable search strategy. This system rigidity, of course, does not allow users to tune models in order to improve the search process. In this paper we target this issue by presenting an extensible formalism to define a wide range of search options so as to customize, improve and/or analyze the search process of constrained object models.

Original languageEnglish
Title of host publicationNew Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
Pages408-414
Number of pages7
DOIs
StatePublished - 2008
Externally publishedYes
Event21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 - Wroclaw, Poland
Duration: 18 Jun 200820 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5027 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
Country/TerritoryPoland
CityWroclaw
Period18/06/0820/06/08

Keywords

  • Constraint Programming
  • Heuristic Search

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