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A mathematical model of uncertain information

  • Chun-Hung Tzeng
Track 2: Artificial Intelligence
Part of the Lecture Notes in Computer Science book series (LNCS, volume 507)

Abstract

This paper introduces a mathematical evidence model for uncertain information in artificial intelligence. Each evidence model contains prior information as well as possible new evidence to appear later. Both Bayesian probability distribution and Dempster-Shafer's ignorance are special evidence models. A concept of independence is also introduced. Dempster-Shafer's combination rule becomes a formula to combine basic probabilities of independent models.

Keywords

Basic Probability Combination Rule Belief Function Basic Probability Assignment Evidence Function 
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.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Chun-Hung Tzeng
    • 1
  1. 1.Computer Science DepartmentBall State UniversityMuncie

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