Advertisement

A practical system for defeasible reasoning and belief revision

  • Maria R. Cravo
  • João P. Martins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 747)

Abstract

We presented a computational system capable of defeasible reasoning, of revising its beliefs, and which uses truth maintenance techniques to maintain its set of beliefs.

An important point of our work is the fact that the nonmonotonic logic, the BR theory, and the BR system were not developed independently, but rather in an unified way. Thus, the logic itself determines the dependencies between propositions, which are essential to BR systems; the BR theory considers SWMC as the underlying logic, and is thus appropriate to guide the changes in the beliefs of a system whose reasoning is based on this logic; the system's reasoning is guided by SWMC, and its updates are based on the BR theory.

Although the underlying formalisms, i.e., the logic and the BR theory, were developed without any particular application in mind, we came to the conclusion that the resulting system can be successfully used in the solution on typical problems of AI, namely in the areas of diagnosis, inheritance, and counterfactual reasoning. This success comes from the combined use of the two formalisms as well as the truth maintenance techniques.

Keywords

Partial Order Belief Revision Default Rule Underlying Logic Nonmonotonic Logic 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brewka G.: Cumulative Default Logic: in defense of nonmonotonic inference rules. Artificial Intelligence 50, N.2, 183–205, 1991.Google Scholar
  2. Cravo M.R.: Raciocínio por Omissão e Revisão de Crenças: Dois Aspectos do Senso Comum. PhD Thesis, Institute Superior Técnico, Lisbon, Portugal, 1992.Google Scholar
  3. Cravo M.R. and Martins J.P.: Being Aware of Assumptions. Proc. Seventh Österreichische Artificial Intelligence Tagung, Kaindl (ed), 137–146, Informatik-Fachberichte 287, Heidelberg, Germany: Springer-Verlag, 1991.Google Scholar
  4. Doyle J.: Rational Belief Revision. Proc. KR 91, 163–174, Morgan Kaufmann Inc., San Mateo, CA, 1991.Google Scholar
  5. Gärdenfors P.: Knowledge in Flux: Modeling the Dynamics of Epistemic States, The MIT Press, Cambridge, MA, 1988.Google Scholar
  6. Nebel B.: Reasoning and Revision in Hybrid Representation Systems. Springer-Verlag, Heidelberg, Germany, 1990.Google Scholar
  7. Shapiro S.C. e Martins J.P.: Recent Advances and Developments: The SNePS 2.1 Report. Current Trends in SNePS — Semantic Network Processing System, Kumar (ed), 1–13, Lecture Notes in Artificial Intelligence 437, Heidelberg, Germany: Springer-Verlag, 1990.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Maria R. Cravo
    • 1
  • João P. Martins
    • 1
  1. 1.Instituto Superior TécnicoLisboaPortugal

Personalised recommendations