Article

SDD: a new canonical representation of propositional knowledge bases

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IJCAI'11: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two

Pages 819 - 826

Published: 16 July 2011 Publication History

Abstract

We identify a new representation of propositional knowledge bases, the Sentential Decision Diagram (SDD), which is interesting for a number of reasons. First, it is canonical in the presence of additional properties that resemble reduction rules of OBDDs. Second, SDDs can be combined using any Boolean operator in polytime. Third, CNFs with n variables and treewidth w have canonical SDDs of size O(n2^w), which is tighter than the bound on OBDDs based on pathwidth. Finally, every OBDD is an SDD. Hence, working with the latter does not preclude the former.

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Published In

IJCAI'11: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two

July 2011

1756 pages

ISBN:9781577355144

Editor:
Toby Walsh
NICTA and University of NSW

Publisher

AAAI Press

Publication History

Published: 16 July 2011

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Darwiche AMarquis P(2022)On Quantifying Literals in Boolean Logic and its Applications to Explainable AIJournal of Artificial Intelligence Research10.1613/jair.1.1275672(285-328)Online publication date: 4-Jan-2022
https://dl.acm.org/doi/10.1613/jair.1.12756
Sievers SHelmert M(2021)Merge-and-ShrinkJournal of Artificial Intelligence Research10.1613/jair.1.1255771(781-883)Online publication date: 10-Sep-2021
https://dl.acm.org/doi/10.1613/jair.1.12557
Waeldchen SMacdonald JHauch SKutyniok G(2021)The Computational Complexity of Understanding Binary Classifier DecisionsJournal of Artificial Intelligence Research10.1613/jair.1.1235970(351-387)Online publication date: 1-May-2021
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Shen YGoyanka ADarwiche AChoi A(2019)Structured Bayesian networksProceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v33i01.33017957(7957-7965)Online publication date: 27-Jan-2019
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Heradio RFernandez-Amoros DMayr-Dorn CEgyed AAtlee JBultan TWhittle J(2019)Supporting the statistical analysis of variability modelsProceedings of the 41st International Conference on Software Engineering10.1109/ICSE.2019.00091(843-853)Online publication date: 25-May-2019
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Shen YChoi ADarwiche AMcIlraith SWeinberger K(2018)Conditional PSDDsProceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence10.5555/3504035.3504823(6433-6442)Online publication date: 2-Feb-2018
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