Abstract
We provide here a simple, yet very general framework that allows us to explain several constraint propagation algorithms in a systematic way. In particular, using the notions commutativity and semi-commutativity, we show how the well-known AC-3, PC-2, DAC and DPC algorithms are instances of a single generic algorithm. The work reported here extends and simplifies that of Apt [1].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Apt, K.R.: The essence of constraint propagation. Theoretical Computer Science 221(1-2), 179–210 (1999), Available via http://xxx.lanl.gov/archive/cs/
Benhamou, F.: Heterogeneous constraint solving. In: Hanus, M., Rodriguez-Artalejo, M. (eds.) ALP 1996. LNCS, vol. 1139, pp. 62–76. Springer, Heidelberg (1996)
Benhamou, F., Older, W.: Applying interval arithmetic to real, integer and Boolean constraints. Journal of Logic Programming 32(1), 1–24 (1997)
Bistarelli, S., Montanari, U., Rossi, F.: Semiring-based constraint satisfaction and optimization. Journal of the ACM 44(2), 201–236 (1997)
Dechter, R.: Bucket elimination: A unifying framework for structure-driven inference. Artificial Intelligence (1999) (to appear)
Dechter, R., Pearl, J.: Network-based heuristics for constraint-satisfaction problems. Artificial Intelligence 34(1), 1–38 (1988)
Dechter, R., van Beek, P.: Local and global relational consistency. Theoretical Computer Science 173(1), 283–308 (1997)
Han, C., Lee, C.: Comments on Mohr and Henderson’s path consistency algorithm. Artificial Intelligence 36, 125–130 (1988)
Mackworth, A.: Consistency in networks of relations. Artificial Intelligence 8(1), 99–118 (1977)
Marriott, K., Stuckey, P.: Programming with Constraints. The MIT Press, Cambridge (1998)
Mohr, R., Henderson, T.C.: Arc-consistency and path-consistency revisited. Artificial Intelligence 28, 225–233 (1986)
Mohr, R., Masini, G.: Good old discrete relaxation. In: Kodratoff, Y. (ed.) Proceedings of the 8th European Conference on Artificial Intelligence (ECAI), pp. 651–656. Pitman Publishers (1988)
Monfroy, E., Réty, J.-H.: Chaotic iteration for distributed constraint propagation. In: Carroll, J., Haddad, H., Oppenheim, D., Bryant, B., Lamont, G. (eds.) Proceedings of The 1999 ACM Symposium on Applied Computing, SAC 1999, San Antonio, Texas, USA, pp. 19–24. ACM Press, New York (1999)
Montanari, U.: Networks of constraints: Fundamental properties and applications to picture processing. Information Science 7(2), 95–132 (1974); Also Technical Report, Carnegie Mellon University (1971)
Saraswat, V.A., Rinard, M., Panangaden, P.: Semantic foundations of concurrent constraint programming. In: Proceedings of the Eighteenth Annual ACM Symposium on Principles of Programming Languages (POPL 1991), pp. 333–352 (1991)
Telerman, V., Ushakov, D.: Data types in subdefinite models. In: Campbell, J.A., Calmet, J., Pfalzgraf, J. (eds.) AISMC 1996. LNCS, vol. 1138, pp. 305–319. Springer, Heidelberg (1996)
Tsang, E.: Foundations of Constraint Satisfaction. Academic Press, London (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Apt, K.R. (1999). The Rough Guide to Constraint Propagation. In: Jaffar, J. (eds) Principles and Practice of Constraint Programming – CP’99. CP 1999. Lecture Notes in Computer Science, vol 1713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48085-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-540-48085-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66626-4
Online ISBN: 978-3-540-48085-3
eBook Packages: Springer Book Archive