A logically sound method for uncertain reasoning with quantified conditionals

  • Gabriele Kern-Isberner
Accepted Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1244)


Conditionals play a central part in knowledge representation and reasoning. Describing certain relationships between antecedents and consequences by “if-then-sentences” their range of expressiveness includes commonsense knowledge as well as scientific statements. In this paper, we present the principles of maximum entropy resp. of minimum cross-entropy (ME-principles) as a logically sound and practicable method for representing and reasoning with quantified conditionals. First the meaning of these principles is made clear by sketching a characterization from a completely conditional-logical point of view. Then we apply the techniques presented to derive ME-deduction schemes and illustrate them by examples in the second part of this paper.


Maximum Entropy Elementary Event Propositional Variable Logical Consistency Probabilistic Conditional 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Gabriele Kern-Isberner
    • 1
  1. 1.Fachbereich InformatikFernUniversität HagenHagenGermany

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