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Query Answering in Belief Logic Programming

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Scalable Uncertainty Management (SUM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5785))

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Abstract

In this paper we introduce a fixpoint semantics for quantitative logic programming, which is able to both combine and correlate evidence from different sources of information. Based on this semantics, we develop efficient algorithms that can answer queries for non-ground programs with the help of an SLD-like procedure. We also analyze the computational complexity of the algorithms and illustrate their uses.

This work is part of the SILK (Semantic Inference on Large Knowledge) project sponsored by Vulcan, Inc.

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Author information

Authors and Affiliations

  1. State University of New York at Stony Brook, Stony Brook, NY, 11794, USA

    Hui Wan & Michael Kifer

Authors
  1. Hui Wan
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  2. Michael Kifer
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Editors and Affiliations

  1. Articial Intelligence Reseach Institute (IIIA), Spanish National Research Council (CSIC), Campus de la Universitat, 08193, Bellaterra, Spain

    Lluís Godo

  2. Department of Electronics, Computer Science and Systems, University of Calabria, Via P. Bucci, 41C, 87036, Rende (CS), Italy

    Andrea Pugliese

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Wan, H., Kifer, M. (2009). Query Answering in Belief Logic Programming . In: Godo, L., Pugliese, A. (eds) Scalable Uncertainty Management. SUM 2009. Lecture Notes in Computer Science(), vol 5785. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04388-8_21

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  • DOI: https://doi.org/10.1007/978-3-642-04388-8_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04387-1

  • Online ISBN: 978-3-642-04388-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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