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Changes of Relational Probabilistic Belief States and Their Computation under Optimum Entropy Semantics

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KI 2013: Advances in Artificial Intelligence (KI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8077))

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Abstract

Coping with uncertain knowledge and changing beliefs is essential for reasoning in dynamic environments. We generalize an approach to adjust probabilistic belief states by use of the relative entropy in a propositional setting to relational languages. As a second contribution of this paper, we present a method to compute such belief changes by considering a dual problem and present first application and experimental results.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, FernUniversität in Hagen, 58084, Hagen, Germany

    Nico Potyka & Christoph Beierle

  2. Dept. of Computer Science, TU Dortmund, 44221, Dortmund, Germany

    Gabriele Kern-Isberner

Authors
  1. Nico Potyka
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  2. Christoph Beierle
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  3. Gabriele Kern-Isberner
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Editor information

Editors and Affiliations

  1. Business Informatics I, University of Trier, 54286, Trier, Germany

    Ingo J. Timm

  2. Institute for Web Science and Technologies, University of Koblenz, Universitätsstr. 1, 56070, Koblenz, Germany

    Matthias Thimm

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Potyka, N., Beierle, C., Kern-Isberner, G. (2013). Changes of Relational Probabilistic Belief States and Their Computation under Optimum Entropy Semantics. In: Timm, I.J., Thimm, M. (eds) KI 2013: Advances in Artificial Intelligence. KI 2013. Lecture Notes in Computer Science(), vol 8077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40942-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-40942-4_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40941-7

  • Online ISBN: 978-3-642-40942-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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