Tuning constrained objects

Ricardo Soto; Laurent Granvilliers

doi:10.1007/978-3-540-69052-8_43

Tuning constrained objects

Ricardo Soto, Laurent Granvilliers

SCHOOL OF COMPUTER ENGINEERING

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
Pages	408-414
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-540-69052-8_43
State	Published - 2008
Event	21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 - Wroclaw, Poland Duration: 18 Jun 2008 → 20 Jun 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5027 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
Country/Territory	Poland
City	Wroclaw
Period	18/06/08 → 20/06/08

Keywords

Constraint Programming
Heuristic Search

Access to Document

10.1007/978-3-540-69052-8_43

Cite this

Soto, R., & Granvilliers, L. (2008). Tuning constrained objects. In New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings (pp. 408-414). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5027 LNAI). https://doi.org/10.1007/978-3-540-69052-8_43

Soto, Ricardo ; Granvilliers, Laurent. / Tuning constrained objects. New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. pp. 408-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Soto, R & Granvilliers, L 2008, Tuning constrained objects. in New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5027 LNAI, pp. 408-414, 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Wroclaw, Poland, 18/06/08. https://doi.org/10.1007/978-3-540-69052-8_43

Tuning constrained objects. / Soto, Ricardo; Granvilliers, Laurent.
New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. p. 408-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5027 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Soto R, Granvilliers L. Tuning constrained objects. In New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings. 2008. p. 408-414. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-69052-8_43

Tuning constrained objects

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