Abstract
Constraint propagation [10,7,5] (CP) is a cornerstone algorithm of constraint programming, mainly devoted to the computation of local consistency properties of constraint satisfaction problems. The abstract formulation of CP is the combination of a set of reduction functions (black-box solvers) on a domain [8,9,2,1]. Intuitively, there is a dependence relation between functions and domains, such that a function must be applied if a domain it depends on is reduced. The essential property of CP is confluence or strategy-independence. In other words, the order solvers are applied does not influence the output characterized in terms of a common fixed-point of the solvers. Owing to this remark, several strategies based on heuristics, data structures, or knowledge of the solvers have been implemented.
This research was carried out while Eric Monfroy was visiting IRIN.
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Granvilliers, L., Monfroy, E. (2000). Constraint Propagation: Between Abstract Models and ad hoc Strategies. In: Dechter, R. (eds) Principles and Practice of Constraint Programming – CP 2000. CP 2000. Lecture Notes in Computer Science, vol 1894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45349-0_39
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DOI: https://doi.org/10.1007/3-540-45349-0_39
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