License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICLP.2011.240
URN: urn:nbn:de:0030-drops-31697
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2011/3169/
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Molinaro, Cristian ; Sliva, Amy ; Subrahmanian, V. S.

Abduction in Annotated Probabilistic Temporal Logic

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Abstract

Annotated Probabilistic Temporal (APT) logic programs are a form of logic programs that allow users to state (or systems to automatically learn)rules of the form ``formula G becomes true K time units after formula F became true with L to U% probability.''
In this paper, we develop a theory of abduction for APT logic programs. Specifically, given an APT logic program Pi, a set of formulas H that can be ``added'' to Pi, and a goal G, is there a subset S of H such that Pi \cup S is consistent and entails the goal G? In this paper, we study the complexity of the Basic APT Abduction Problem (BAAP). We then leverage a geometric characterization of BAAP to suggest a set of pruning strategies when solving BAAP and use these intuitions to develop a sound and complete algorithm.

BibTeX - Entry

@InProceedings{molinaro_et_al:LIPIcs:2011:3169,
  author =	{Cristian Molinaro and Amy Sliva and V. S. Subrahmanian},
  title =	{{Abduction in Annotated Probabilistic Temporal Logic}},
  booktitle =	{Technical Communications of the 27th International Conference on Logic Programming (ICLP'11) },
  pages =	{240--250},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-31-6},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{11},
  editor =	{John P. Gallagher and Michael Gelfond},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2011/3169},
  URN =		{urn:nbn:de:0030-drops-31697},
  doi =		{10.4230/LIPIcs.ICLP.2011.240},
  annote =	{Keywords: Probabilistic Reasoning, Imprecise Probabilities, Temporal Reasoning, Abductive Reasoning}
}

Keywords: Probabilistic Reasoning, Imprecise Probabilities, Temporal Reasoning, Abductive Reasoning
Collection: Technical Communications of the 27th International Conference on Logic Programming (ICLP'11)
Issue Date: 2011
Date of publication: 27.06.2011

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