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Using probability-density functions in the framework of evidential reasoning

  • Section II Approaches To Uncertainty A) Evidence Theory
  • Conference paper
  • First Online:
Uncertainty in Knowledge-Based Systems (IPMU 1986)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 286))

Abstract

To develop an approach to utilizing continuous statistical information within the Dempster-Shafer framework, we combine methods proposed by Strat and by Shafer. We first derive continuous possibility and mass functions from probability-density functions. Then we propose a rule for combining such evidence that is simpler and can be computed more efficiently than Dempster's rule. We discuss the relationship between Dempster's rule and our proposed rule for combining evidence over continuous frames.

The work reported here was supported in part by the Defense Advanced Research Projects Agency under Contract MDA903-83-C-0027 and in part by the Ecole Nationale Supérieure des Télécommunications.

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References

  1. G.A. Shafer, A Mathematical Theory of Evidence, pp. 237–250 (Princeton University Press, Princeton, New Jersey, 1976).

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  2. T.M. Strat and J.D. Lowrance, “Evidential Reasoning with Continuous Variables,” Technical Note, Artificial Intelligence Center, SRI International, Menlo Park, California (forthcoming).

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  3. T.M. Strat, “Continuous Belief Functions for Evidential Reasoning,” Proceedings, AAAI-84, Austin, Texas (August 1984).

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  4. G.A. Shafer, “Belief Functions and Possibility Measures,” University of Kansas, School of Business Working Paper No. 163 (September 1984).

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  5. L.A. Zadeh, “A Theory of Approximate Reasoning,” Machine Intelligence 9 (John Wiley and Sons, Inc., New York, New York, 1979).

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  6. G. Reynolds, D. Strahman, N. Lehrer, “Converting Feature Values to Evidence,” pp. 331–338, Proceedings of the Image Understanding Workshop, Miami, Florida (December 1985).

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Authors and Affiliations

  1. Artificial Intelligence Center, SRI International, 333 Ravenswood Avenue, 94025, Menlo Park, California

    Pascal V. Fua

Authors
  1. Pascal V. Fua
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Editor information

B. Bouchon R. R. Yager

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© 1987 Springer-Verlag Berlin Heidelberg

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Fua, P.V. (1987). Using probability-density functions in the framework of evidential reasoning. In: Bouchon, B., Yager, R.R. (eds) Uncertainty in Knowledge-Based Systems. IPMU 1986. Lecture Notes in Computer Science, vol 286. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-18579-8_9

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  • DOI: https://doi.org/10.1007/3-540-18579-8_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-18579-6

  • Online ISBN: 978-3-540-48020-4

  • eBook Packages: Springer Book Archive

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