Structured belief bases: A practical approach to prioritised base revision

  • Dov Gabbay
  • Odinaldo Rodrigues
Accepted Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1244)


In this paper we present Structured Belief Bases (SBBs), a framework to reason about belief change. Structured Belief Bases can be considered as a special case of prioritised base revision, where the components of the base are allowed to be structured bases as well. This allows for the representation of complex levels of priority between sentences. Each component is resolved into a sentence via a revision operator taking the ordering into account. By adopting a right associative interpretation of the operator we avoid many of the problems with iteration faced by revision operators complying with the AGM postulates. New beliefs can be accepted by simply incorporating them into the base with highest priority.


Propositional Logic Epistemic State Belief Revision Belief State Integrity Constraint 
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  1. 1.
    Karl Hans Bläsius and Hans-Jürgen Bürckert. Deduction Systems in Artificial Intelligence. Ellis Horwood Limited, 1989.Google Scholar
  2. 2.
    M. Dalal. Investigations into a theory of knowledge base revision: Preliminary report. Proceedings of the 7th National Conference on Artificial Intelligence, pages 475–479, 1988.Google Scholar
  3. 3.
    Dov Gabbay and Odinaldo Rodrigues. A methodology for iterated theory change. In Dov M. Gabbay and Hans Jürgen Ohlbach, editors, Practical Reasoning — First International Conference on Formal and Applied Practical Reasoning, FAPR'96, Lecture Notes in Artificial Intelligence. Springer Verlag, 1996.Google Scholar
  4. 4.
    P. Gärdenfors and Hans Rott. Belief revision. In C. J. Hogger Dov Gabbay and J. A. Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, volume 4, pages 35–132. Oxford University Press, 1995.Google Scholar
  5. 5.
    Peter Gärdenfors. Knowledge in Flux: Modeling the Dynamics of Epistemic States. A Bradford Book-The MIT Press, Cambridge, Massachusetts-London, England, 1988.Google Scholar
  6. 6.
    Hirofumi Katsuno and Alberto O. Mendelzon. On the difference between updating a knowledge base and revising it. Belief Revision, pages 183–203, 1992.Google Scholar
  7. 7.
    Bernhard Nebel. Belief revision and default reasoning: Syntax-based approaches. In J. Allen, R. Fikes, and E. Sandewall, editors, Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning, pages 417–428. Morgan Kaufmann, 1991.Google Scholar
  8. 8.
    Ilkka Niiniluoto. Truthlikeness. Kluwer Academic Publishers, 1989.Google Scholar
  9. 9.
    Odinaldo Rodrigues. Transfer report: Mphil/phd. Imperial College of Science, Technology and Medicine, February 1996. Department of Computing.Google Scholar
  10. 10.
    Odinaldo Rodrigues. A methodology for iterated information change. PhD thesis, Department of Computing, Imperial College, To appear.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Dov Gabbay
    • 1
  • Odinaldo Rodrigues
    • 1
  1. 1.Department of ComputingImperial CollegeLondonUK

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