Towards Leveraging Backdoors in Qualitative Constraint Networks

Michael Sioutis*, Tomi Janhunen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationKI 2019
Subtitle of host publicationAdvances in Artificial Intelligence - 42nd German Conference on AI, Proceedings
EditorsChristoph Benzmüller, Heiner Stuckenschmidt
Number of pages8
ISBN (Print)9783030301781
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Conference publication
EventGerman Conference on Artificial Intelligence - Kassel, Germany
Duration: 23 Sept 201926 Sept 2019
Conference number: 42

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11793 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceGerman Conference on Artificial Intelligence
Abbreviated titleKI


  • Backbones
  • Backdoors
  • Local consistencies
  • Qualitative constraints
  • Spatio-temporal reasoning


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