In this short paper we introduce the notions of backbones and backdoors in the context of qualitative constraint networks. As motivation for the study of those structures, we argue that they can be used to define collaborative approaches among SAT, CP, and native tools, inspire novel decomposition and parallelization techniques, and lead to the development of adaptive constraint propagators with a better insight into the particularities of real-world datasets than what is possible today.
CITATION STYLE
Sioutis, M., & Janhunen, T. (2019). Towards Leveraging Backdoors in Qualitative Constraint Networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11793 LNAI, pp. 308–315). Springer Verlag. https://doi.org/10.1007/978-3-030-30179-8_27
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