Probabilisitc Logic Programming under Maximum Entropy

  • Thomas Lukasiewicz
  • Gabriele Kern-Isberner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1638)


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.


Logic Program Maximum Entropy Linear Constraint Probabilistic Logic Atomic Formula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Thomas Lukasiewicz
    • 1
  • Gabriele Kern-Isberner
    • 2
  1. 1.Institut für Informatik, Universität GießenGießenGermany
  2. 2.Fachbereich Informatik, FernUniversität HagenHagenGermany

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