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Original Articles

Approximating Belief Functions in a Rule-Based System

Pages 211-228 | Published online: 14 Aug 2013

  • BarnettJ.A. (1981). Computational methods for a mathematical theory of evidence. Proceedings of the National Conference on Artificial Intelligence, 868–875.
  • BlackP. (1987). Representing and updating uncertainty in an expert system. Ph.D. Thesis Proposal. Department of Statistics, Carnegie Mellon University.
  • ChowC.K. and LiuC.N. (1968). Approximating discrete probability distributuions with dependence trees. IEEE Transactions on Information Theory, IT–14, 462–467.
  • EddyW.F. and PeiG.P. (1986). Structures of rule-based belief functions. IBM Journal of Research and Development, 30, 93–101.
  • KybergH.E.Jr. (1987). Bayesian and non-Bayesian evidential updating. Artificial Intelligence, 31, No. 3, 271–293.
  • ShaferG. (1976). A Mathematical Theory of Evidence. Princeton University Press, PrincetonNew Jersey.
  • SpiegelhalterD.J. (1986). Coherent evidence propogation in expert systems. Talk presented at the International Workshop on Bayesian Methodology, StresaItaly.

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