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The Complexity of Plate Probabilistic Models

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Scalable Uncertainty Management (SUM 2015)

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

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Abstract

Plate-based probabilistic models combine a few relational constructs with Bayesian networks, so as to allow one to specify large and repetitive probabilistic networks in a compact and intuitive manner. In this paper we investigate the combined, data and domain complexity of plate models, showing that they range from polynomial to \(\#\mathsf {P}\)-complete to \(\#\mathsf {EXP}\)-complete.

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Notes

  1. 1.

    Note that the definition of plate model in Ref. [10] does not require acyclicity, but this seems to be a necessary requirement in all the relevant literature.

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Acknowledgements

The first author was partially supported by CNPq and the second author was partially supported by FAPESP.

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Authors and Affiliations

  1. Universidade de São Paulo, São Paulo, Brazil

    Fabio G. Cozman & Denis D. Mauá

Authors
  1. Fabio G. Cozman
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  2. Denis D. Mauá
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Correspondence to Fabio G. Cozman .

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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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Cozman, F.G., Mauá, D.D. (2015). The Complexity of Plate Probabilistic Models. 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_3

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  • DOI: https://doi.org/10.1007/978-3-319-23540-0_3

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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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