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Knowledge Compilation for Belief Change

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Book cover AI 2006: Advances in Artificial Intelligence (AI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4304))

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Abstract

Techniques for knowledge compilation like prime implicates and binary decision diagrams (BDDs) are effective methods for improving the practical efficiency of reasoning tasks. In this paper we provide a construction for a belief contraction operator using prime implicates. We also briefly indicate how this technique can be used for belief expansion, belief revision and also iterated belief change. This simple yet novel technique has two significant features: (a) the contraction operator constructed satisfies all the AGM postulates for belief contraction; (b) when compilation has been effected only syntactic manipulation is required in order to contract the reasoner’s belief state.

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Author information

Authors and Affiliations

  1. ARC Centre of Excellence for Autonomous Systems and National ICT Australia, School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW, 2052, Australia

    Maurice Pagnucco

Authors
  1. Maurice Pagnucco
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Editor information

Editors and Affiliations

  1. DisPRR, National ICT Australia Ltd, QLD, Australia

    Abdul Sattar

  2. School of Computing, University of Tasmania, Sandy Bay, 7005, Tasmania, Australia

    Byeong-ho Kang

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© 2006 Springer-Verlag Berlin Heidelberg

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Pagnucco, M. (2006). Knowledge Compilation for Belief Change. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_13

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  • DOI: https://doi.org/10.1007/11941439_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49787-5

  • Online ISBN: 978-3-540-49788-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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