Promoting constraints to first-class status
Identifieur interne :
000004 ( PascalFrancis/Curation );
précédent :
000003;
suivant :
000005
Promoting constraints to first-class status
Auteurs : T. Müller [
Allemagne]
Source :
-
Lecture notes in computer science [ 0302-9743 ] ; 2000.
RBID : Pascal:00-0474257
Descripteurs français
English descriptors
Abstract
This paper proposes to promote constraints to first-class status. In contrast to constraint propagation, which performs inference on values of variables, first-class constraints allow reasoning about the constraints themselves. This lets the programmer access the current state of a constraint and control a constraint's behavior directly, thus making powerful new programming and inference techniques possible, as the combination of constraint propagation and rewriting constraints à la term rewriting. First-class constraints allow for true meta constraint programming. Promising applications in the field of combinatorial optimization include early unsatisfiability detection, constraint reformulation to improve propagation, garbage collection of redundant but not yet entailed constraints, and finding minimal inconsistent subsets of a given set of constraints for debugging immediately failing constraint programs. We demonstrate the above-mentioned applications by means of examples. The experiments were done with Mozart Oz but can be easily ported to other constraint solvers.
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| A08 | 01 | 1 | ENG | @1 Promoting constraints to first-class status |
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| A09 | 01 | 1 | ENG | @1 CL 2000 : computational logic : London, 24-28 July 2000 |
|---|
| A11 | 01 | 1 | | @1 MÜLLER (T.) |
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| A12 | 01 | 1 | | @1 LLOYD (John) @9 ed. |
|---|
| A12 | 02 | 1 | | @1 DAHL (Veronica) @9 ed. |
|---|
| A12 | 03 | 1 | | @1 FURBACH (Ulrich) @9 ed. |
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| A12 | 04 | 1 | | @1 KERBER (Manfred) @9 ed. |
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| A12 | 05 | 1 | | @1 KUNG-KIU LAU @9 ed. |
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| A12 | 06 | 1 | | @1 PALAMIDESSI (Catuscia) @9 ed. |
|---|
| A12 | 07 | 1 | | @1 PEREIRA (Luís Moniz) @9 ed. |
|---|
| A12 | 08 | 1 | | @1 SAGIV (Yehoshua) @9 ed. |
|---|
| A12 | 09 | 1 | | @1 STUCKEY (Peter J.) @9 ed. |
|---|
| A14 | 01 | | | @1 Programming System Lab, Universität des Saarlandes, Postfach 15 11 50 @2 66041 Saarbrücken @3 DEU @Z 1 aut. |
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| A43 | 01 | | | @1 INIST @2 16343 @5 354000090070640290 |
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| A44 | | | | @0 0000 @1 © 2000 INIST-CNRS. All rights reserved. |
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| A45 | | | | @0 19 ref. |
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| A66 | 02 | | | @0 USA |
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| C01 | 01 | | ENG | @0 This paper proposes to promote constraints to first-class status. In contrast to constraint propagation, which performs inference on values of variables, first-class constraints allow reasoning about the constraints themselves. This lets the programmer access the current state of a constraint and control a constraint's behavior directly, thus making powerful new programming and inference techniques possible, as the combination of constraint propagation and rewriting constraints à la term rewriting. First-class constraints allow for true meta constraint programming. Promising applications in the field of combinatorial optimization include early unsatisfiability detection, constraint reformulation to improve propagation, garbage collection of redundant but not yet entailed constraints, and finding minimal inconsistent subsets of a given set of constraints for debugging immediately failing constraint programs. We demonstrate the above-mentioned applications by means of examples. The experiments were done with Mozart Oz but can be easily ported to other constraint solvers. |
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| C02 | 01 | X | | @0 001D02C05 |
|---|
| C03 | 01 | X | FRE | @0 Programmation logique avec contrainte @5 01 |
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| C03 | 01 | X | ENG | @0 Constraint logic programming @5 01 |
|---|
| C03 | 01 | X | SPA | @0 Programación lógica con restricción @5 01 |
|---|
| C03 | 02 | X | FRE | @0 Optimisation combinatoire @5 02 |
|---|
| C03 | 02 | X | ENG | @0 Combinatorial optimization @5 02 |
|---|
| C03 | 02 | X | SPA | @0 Optimización combinatoria @5 02 |
|---|
| C03 | 03 | X | FRE | @0 Transformation programme @5 03 |
|---|
| C03 | 03 | X | ENG | @0 Program transformation @5 03 |
|---|
| C03 | 03 | X | SPA | @0 Transformación programa @5 03 |
|---|
| C03 | 04 | X | FRE | @0 Optimisation programme @5 04 |
|---|
| C03 | 04 | X | ENG | @0 Program optimization @5 04 |
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| C03 | 04 | X | SPA | @0 Optimización programa @5 04 |
|---|
| C03 | 05 | X | FRE | @0 Résolution problème @5 05 |
|---|
| C03 | 05 | X | ENG | @0 Problem solving @5 05 |
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| C03 | 05 | X | SPA | @0 Resolución problema @5 05 |
|---|
| N21 | | | | @1 318 |
|---|
|
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| pR |
| A30 | 01 | 1 | ENG | @1 Computational logic. International conference @2 1 @3 London GBR @4 2000-07-24 |
|---|
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Le document en format XML
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</keywords><front><div type="abstract" xml:lang="en">This paper proposes to promote constraints to first-class status. In contrast to constraint propagation, which performs inference on values of variables, first-class constraints allow reasoning about the constraints themselves. This lets the programmer access the current state of a constraint and control a constraint's behavior directly, thus making powerful new programming and inference techniques possible, as the combination of constraint propagation and rewriting constraints à la term rewriting. First-class constraints allow for true meta constraint programming. Promising applications in the field of combinatorial optimization include early unsatisfiability detection, constraint reformulation to improve propagation, garbage collection of redundant but not yet entailed constraints, and finding minimal inconsistent subsets of a given set of constraints for debugging immediately failing constraint programs. We demonstrate the above-mentioned applications by means of examples. The experiments were done with Mozart Oz but can be easily ported to other constraint solvers.</div>
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