Abstract
Classical constraint satisfaction problems (CSPs) provide an expressive formalism for modeling and solving many real-world problems. However, classical CSPs prove to be restrictive in any situation where uncertainty, fuzziness, probability, optimisation or partial satisfaction are intrinsic. Soft constraints alleviate many of the restrictions which classical constraint satisfaction impose. In particular, soft constraints provide a basis for capturing notions such as vagueness, uncertainty and cost in the CSP model.
This work has received support from Enterprise Ireland under their Basic Research Grant Scheme (Grant Number SC/02/289).
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Kelleher, J., O’Sullivan, B. (2003). Optimising the Representation and Evaluation of Semiring Combination Constraints. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_102
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