Interchangeability supports abstraction and reformulation for multi-dimensional constraint satisfaction

Authors:
Eugene C. Freuder;Daniel Sabin
Affiliations:
Department of Computer Science, University of New Hampshire, Durham, NH;Department of Computer Science, University of New Hampshire, Durham, NH
Venue:
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Year:
1997

Citing 4
Cited 11

Constraint satisfaction with a multi-dimensional domain

Proceedings of the first international conference on Artificial intelligence planning systems
Dual viewpoint heuristics for binary constraint satisfaction problems

ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Representation Selection for Constraint Satisfaction: A Case Study Using n-Queens

IEEE Expert: Intelligent Systems and Their Applications
Abstraction via approximate symmetry

IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 2

A Context for Constraint Satisfaction Problem Formulation Selection

Constraints
Product Configuration Frameworks-A Survey

IEEE Intelligent Systems
A CSP Abstraction Framework

SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Abstracting Soft Constraints

Selected papers from the Joint ERCIM/Compulog Net Workshop on New Trends in Contraints
How the Level of Interchangeability Embedded in a Finite Constraint Satisfaction Problem Affects the Performance of Search

AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Introduction to the special volume on reformulation

Artificial Intelligence - Special volume on reformulation
Automated reformulation of specifications by safe delay of constraints

Artificial Intelligence
Evaluating ASP and Commercial Solvers on the CSPLib

Constraints
Parametric abstraction of behavioral modes for model-based diagnosis

AI Communications
Neighborhood interchangeability and dynamic bundling for non-binary finite CSPs

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Relaxation of qualitative constraint networks

SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Interchangeability provides a principled approach to abstraction and reformulation of constraint satisfaction problems. Values are interchangeable if exchanging one for the other in any solution produces another solution. Abstracting a problem by simplifying the constraints can increase interchangeability. Multi-dimensional constraint satisfaction problems can provide natural opportunities for this abstraction process. Multi-dimensional problems may involve vectors of values, or conjunctive constraints. Utilizing the interchangeability can permit more efficient solutions of the abstracted problem. These solutions can be expanded into smaller reformulations of the original problem. Solving abstracted and then reformulated problems can be considerably more efficient than solving the original problems. We provide data that demonstrates the potential of this abstraction/reformulation process for multi-dimensional problems, and illuminates how its utility can depend on natural problem parameters.