Generating custom propagators for arbitrary constraints
- Submitting institution
-
University of St Andrews
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 252010833
- Type
- D - Journal article
- DOI
-
10.1016/j.artint.2014.03.001
- Title of journal
- Artificial Intelligence
- Article number
- -
- First page
- 1
- Volume
- 211
- Issue
- -
- ISSN
- 0004-3702
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
A - Artificial Intelligence
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Efficient constraint propagation algorithms are central to the performance of state-of-the-art constraint solvers. Given the rich language that constraint programming provides, a significant problem in the field is designing and implementing constraint propagators for the very large set of possible constraints. This paper demonstrates how this process can be automated to produce very efficient propagators. It has received considerable interest, with other researchers extending it in several ways, including work on building transducers, optimised tables, reformulation and compilation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
