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A mathematical model of uncertain information

  • Track 2: Artificial Intelligence
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Computing in the 90's (Great Lakes CS 1989)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 507))

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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.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, Ball State University, 47306, Muncie, IN

    Chun-Hung Tzeng

Authors
  1. Chun-Hung Tzeng
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Editor information

Naveed A. Sherwani Elise de Doncker John A. Kapenga

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© 1991 Springer-Verlag Berlin Heidelberg

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Tzeng, CH. (1991). A mathematical model of uncertain information. In: Sherwani, N.A., de Doncker, E., Kapenga, J.A. (eds) Computing in the 90's. Great Lakes CS 1989. Lecture Notes in Computer Science, vol 507. Springer, New York, NY. https://doi.org/10.1007/BFb0038473

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  • DOI: https://doi.org/10.1007/BFb0038473

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97628-0

  • Online ISBN: 978-0-387-34815-5

  • eBook Packages: Springer Book Archive

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