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International Conference on Scalable Uncertainty Management

SUM 2015: Scalable Uncertainty Management pp 83–98Cite as

On the Impact of Junction-Tree Topology on Weighted Model Counting

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9310))

Abstract

We present and evaluate the power of a new framework for weighted model counting and inference in graphical models, based on exploiting the topology of the junction tree representing the formula. The proposed approach uses the junction tree topology in order to craft a reduced set of partial assignments that are guaranteed to decompose the formula. We show that taking advantage of the junction tree structure, along with existing optimization methods borrowed from the CNF-SAT domain, can translate into significant time savings for weighted model counting algorithms.

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Notes

  1. 1.

    Available online at http://www.cs.huji.ac.il/project/PASCAL/showNet.php.

  2. 2.

    Available online at http://reasoning.cs.ucla.edu/ace/.

  3. 3.

    Code is available at: https://github.com/batyak/PROSaiCO/.

  4. 4.

    http://graphmod.ics.uci.edu/uai08/Evaluation/Report/Benchmarks.

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Acknowledgments

The work was carried out in and partially supported by the Technion–Microsoft Electronic Commerce research center.

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Authors and Affiliations

  1. Technion, Israel Institute of Technology, Haifa, Israel

    Batya Kenig & Avigdor Gal

Authors
  1. Batya Kenig
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  2. Avigdor Gal
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Correspondence to Batya Kenig .

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Editors and Affiliations

  1. Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Hagen, Germany

    Christoph Beierle

  2. California Polytechnic State University, SAN LUIS OBISPO, USA

    Alex Dekhtyar

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Kenig, B., Gal, A. (2015). On the Impact of Junction-Tree Topology on Weighted Model Counting. In: Beierle, C., Dekhtyar, A. (eds) Scalable Uncertainty Management. SUM 2015. Lecture Notes in Computer Science(), vol 9310. Springer, Cham. https://doi.org/10.1007/978-3-319-23540-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-23540-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23539-4

  • Online ISBN: 978-3-319-23540-0

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