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Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm

  • Marcel Gehrke
  • Tanya Braun
  • Ralf Möller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11320)

Abstract

The lifted dynamic junction tree algorithm (LDJT) answers filtering and prediction queries efficiently for probabilistic relational temporal models by building and then reusing a first-order cluster representation of a knowledge base for multiple queries and time steps. Unfortunately, a non-ideal elimination order can lead to groundings. We extend LDJT (i) to identify unnecessary groundings and (ii) to prevent groundings by delaying eliminations through changes in a temporal first-order cluster representation. The extended version of LDJT answers multiple temporal queries orders of magnitude faster than the original version.

References

  1. 1.
    Braun, T., Möller, R.: Preventing groundings and handling evidence in the lifted junction tree algorithm. In: Kern-Isberner, G., Fürnkranz, J., Thimm, M. (eds.) KI 2017. LNCS (LNAI), vol. 10505, pp. 85–98. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-67190-1_7CrossRefGoogle Scholar
  2. 2.
    Gehrke, M., Braun, T., Möller, R.: Towards preventing unnecessary groundings in the lifted dynamic junction tree algorithm. In: Trollmann, F., Turhan, A.Y. (eds.) KI 2018. LNCS, pp. 38–45. Springer, Cham (2018).  https://doi.org/10.1007/978-3-030-00111-7_4CrossRefGoogle Scholar
  3. 3.
    Taghipour, N.: Lifted probabilistic inference by variable elimination. Ph.D. thesis, KU Leuven (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Institute of Information SystemsUniversity of LübeckLübeckGermany

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