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A Declarative Approach for Computing Ordinal Conditional Functions Using Constraint Logic Programming

  • Christoph BeierleEmail author
  • Gabriele Kern-Isberner
  • Karl Södler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7773)

Abstract

In order to give appropriate semantics to qualitative conditionals of the form if A then normally B, ordinal conditional functions (OCFs) ranking the possible worlds according to their degree of plausibility can be used. An OCF accepting all conditionals of a knowledge base R can be characterized as the solution of a constraint satisfaction problem. We present a high-level, declarative approach using constraint logic programming (CLP) techniques for solving this constraint satisfaction problem. In particular, the approach developed here supports the generation of all minimal solutions; this also holds for different notions of minimality which we discuss and implement in CLP. Minimal solutions are of special interest as they provide a basis for model-based inference from R.

Keywords

Ranking Function Constraint Satisfaction Problem Epistemic State Minimal Solution Propositional 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 2013

Authors and Affiliations

  • Christoph Beierle
    • 1
    Email author
  • Gabriele Kern-Isberner
    • 2
  • Karl Södler
    • 1
  1. 1.Department of Computer ScienceFernUniversität in HagenHagenGermany
  2. 2.Department of Computer ScienceTU DortmundDortmundGermany

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