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Reasoning over Linear Probabilistic Knowledge Bases with Priorities

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Scalable Uncertainty Management (SUM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9310))

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Abstract

We consider the problem of reasoning over probabilistic knowledge bases with different priority levels. While we assume that the knowledge is consistent on each level, there can be inconsistencies between different levels. Examples arise naturally in hierarchical domains when general knowledge is overwritten with more specific information. We extend recent results on inconsistency-tolerant probabilistic reasoning to propose a solution for this problem.

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Notes

  1. 1.

    https://www.fernuni-hagen.de/wbs/research/log4kr/index.html.

  2. 2.

    http://ojalgo.org/.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Fern Universität in Hagen, Hagen, Germany

    Nico Potyka

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  1. Nico Potyka
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Correspondence to Nico Potyka .

Editor information

Editors and Affiliations

  1. Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Hagen, Germany

    Christoph Beierle

  2. California Polytechnic State University, SAN LUIS OBISPO, USA

    Alex Dekhtyar

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Potyka, N. (2015). Reasoning over Linear Probabilistic Knowledge Bases with Priorities. In: Beierle, C., Dekhtyar, A. (eds) Scalable Uncertainty Management. SUM 2015. Lecture Notes in Computer Science(), vol 9310. Springer, Cham. https://doi.org/10.1007/978-3-319-23540-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-23540-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23539-4

  • Online ISBN: 978-3-319-23540-0

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