Towards Leveraging Backdoors in Qualitative Constraint Networks

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

Researchers

Research units

  • Tampere University

Abstract

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.

Details

Original languageEnglish
Title of host publicationKI 2019
Subtitle of host publicationAdvances in Artificial Intelligence - 42nd German Conference on AI, Proceedings
EditorsChristoph Benzmüller, Heiner Stuckenschmidt
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Article in a conference publication
EventGerman Conference on Artificial Intelligence - Kassel, Germany
Duration: 23 Sep 201926 Sep 2019
Conference number: 42

Publication series

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

Conference

ConferenceGerman Conference on Artificial Intelligence
Abbreviated titleKI
CountryGermany
CityKassel
Period23/09/201926/09/2019

    Research areas

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

ID: 37822652