The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Principles of Constraint Programming
Abstract
Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list of references will also be valuable to professionals in computer science and artificial intelligence.
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Cites
Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
Genetic Algorithms + Data Structures = Evolution Programs
Michalewicz, Z. (1992) · Artificial Intelligence · doi:10.1007/978-3-662-02830-8 · Cited by 11,553
Maintaining knowledge about temporal intervals
Allen, J. F. (1983) · Communications of the ACM · doi:10.1145/182.358434 · Cited by 7,593 · cited 6×
“6 and the ensuing temporal CSP’s were introduced in Allen (1983). The eight spatial relations presented in Figure 2.7 and the composition table given in Figure 2.8 were introduced in Egenhofer (1991). In Egenhofer (1994a) these relations were systematically derived and in Egenhofer (1994b) a connection with the CSP’s…”
InfluentialDepth-First Search and Linear Graph Algorithms
Tarjan, R. (1972) · SIAM Journal on Computing · doi:10.1137/0201010 · Cited by 6,081
A Machine-Oriented Logic Based on the Resolution Principle
Robinson, J. A. (1965) · Journal of the ACM · doi:10.1145/321250.321253 · Cited by 3,909
A Computing Procedure for Quantification Theory
Davis, M., & Putnam, H. (1960) · Journal of the ACM · doi:10.1145/321033.321034 · Cited by 2,647
Baader, F., & Nipkow, T. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9781139172752 · Cited by 2,466
Consistency in networks of relations
Mackworth, A. K. (1977) · Artificial Intelligence · doi:10.1016/0004-3702(77)90007-8 · Cited by 2,458
Global Optimization Using Interval Analysis
(2003) · CRC Press eBooks · doi:10.1201/9780203026922 · Cited by 1,674
Foundations of Constraint Satisfaction
(1993) · Elsevier eBooks · doi:10.1016/c2013-0-07627-x · Cited by 1,603
Cited by
Review of Optimization Strategies for System-Level Design in Hybrid Electric Vehicles
Silvas, E., Hofman, T., Murgovski, N., Etman, P., & Steinbuch, M. (2016) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2016.2547897 · Cited by 323
Metadata
- Authors
- Apt, K.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2003-08-28
- OpenAlex
- W1733489975
- Cited by
- 888
- References
- 46
- FWCI
- 32.97
- Type
- book
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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