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Logical Particle Filtering

Authors: Luke S. Zettlemoyer, Hanna M. Pasula, and Leslie Pack Kaelbling

Published in: Dagstuhl Seminar Proceedings, Volume 7161, Probabilistic, Logical and Relational Learning - A Further Synthesis (2008)

Abstract

In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical particle filtering algorithm. Each particle contains a logical formula that describes a set of states. The algorithm updates the formulae as new observations are received. Since a single particle tracks many states, this filter can be more accurate than a traditional particle filter in high dimensional state spaces, as we demonstrate in experiments.

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Luke S. Zettlemoyer, Hanna M. Pasula, and Leslie Pack Kaelbling. Logical Particle Filtering. In Probabilistic, Logical and Relational Learning - A Further Synthesis. Dagstuhl Seminar Proceedings, Volume 7161, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{zettlemoyer_et_al:DagSemProc.07161.5,
  author =	{Zettlemoyer, Luke S. and Pasula, Hanna M. and Pack Kaelbling, Leslie},
  title =	{{Logical Particle Filtering}},
  booktitle =	{Probabilistic, Logical and Relational Learning - A Further Synthesis},
  pages =	{1--14},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{7161},
  editor =	{Luc de Raedt and Thomas Dietterich and Lise Getoor and Kristian Kersting and Stephen H. Muggleton},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07161.5},
  URN =		{urn:nbn:de:0030-drops-13792},
  doi =		{10.4230/DagSemProc.07161.5},
  annote =	{Keywords: Particle filter, logical hidden Markov model}
}

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Logical Particle Filtering

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