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Probabilisitc Logic Programming under Maximum Entropy

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Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1638))

Abstract

In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by defining probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an efficient linear programming characterization for the problem of deciding whether a probabilistic logic program is satisfiable. Finally, and as a central contribution of this paper, we introduce an efficient technique for approximative probabilistic logic programming under maximum entropy. This technique reduces the original entropy maximization task to solving a modified and relatively small optimization problem.

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Author information

Authors and Affiliations

  1. Institut für Informatik, Universität Gießen, Arndtstraße 2, D-35392, Gießen, Germany

    Thomas Lukasiewicz

  2. Fachbereich Informatik, FernUniversität Hagen, P.O. Box 940, D-58084, Hagen, Germany

    Gabriele Kern-Isberner

Authors
  1. Thomas Lukasiewicz
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  2. Gabriele Kern-Isberner
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, UK

    Anthony Hunter

  2. Department of Electronic Engineering, University of London, Queen Mary and Westfield College, E1 4NS, London, UK

    Simon Parsons

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© 1999 Springer-Verlag Berlin Heidelberg

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Lukasiewicz, T., Kern-Isberner, G. (1999). Probabilisitc Logic Programming under Maximum Entropy. In: Hunter, A., Parsons, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1999. Lecture Notes in Computer Science(), vol 1638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48747-6_26

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  • DOI: https://doi.org/10.1007/3-540-48747-6_26

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  • Print ISBN: 978-3-540-66131-3

  • Online ISBN: 978-3-540-48747-0

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