Re: Dempster-Shafer question

Johan Schubert (johans@atlas.sto.foa.se)
Tue, 24 Mar 1998 02:02:00 +0100 (MET)

In article <6emmlt$3t3$1@nnrp1.dejanews.com>, craig_jacobs@asl-tk.com writes:
|> I was wondering if anyone out there could point me to any good articles,
|> books or web-sites that talk about Dempster-Shafer Theory
|>
|> Thanks in Advance
|> Craig Jacobs
|>
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Craig, here are some good referenses:

OVERVIEW:

Shafer, G., Perspectives on the Theory and Practice of Belief
Functions, Int. J. Approx. Reasoning 4(5/6), 323-362, 1990.

Pearl, J., Reasoning with Belief Functions: An Analysis of
Compatibility, Int. J. Approx. Reasoning 4(5/6), 363-389, 1990.

Shafer, G., Rejoinders to Comments on "Perspectives on the Theory and
Practice of Belief Functions", Int. J. Approx. Reasoning 6(3),
445-480, 1992.

Klir, G. J., Probabilistic Versus Possibilistic Conceptualization of
Uncertainty, in Analysis and Management of Uncertainty: Theory and
Applications, Machine Intelligence and Pattern Recognition Ser.,
Vol. 13 (B.M. Ayyub, M.M. Gupta and L.N. Kanal, Eds.), Elsevier
Science Publ. (North-Holland), Amsterdam, 13-25, 1992.

GENERAL:

Shafer, G., A Mathematical Theory of Evidence, Princeton University
Press, Princeton, N.J., 1976.

Yager, R.Y., Fedrizzi, M., and Kacprzyk, J., Eds., Advances in the
Dempster-Shafer Theory of Evidence, John Wiley & Sons, Inc., New York,
1994. ISBN 0-471-55248-8.

FAST CALCULATION:

Barnett, J. A., Computational Methods for a Mathematical Theory of
Evidence, Proceedings of the 7th International Joint Conference on AI,
Vancouver, BC, 868-875, 1981.

Kennes, R., and Smets, P., Computational Aspects of the Möbius
Transformation, in Uncertainty in Artificial Intelligence 6, Machine
Intelligence and Pattern Recognition Ser., Vol. 12 (P.P. Bonissone,
M. Henrion, L.N. Kanal and J.F. Lemmer, Eds.), Elsevier Science
Publ. (North-Holland), Amsterdam, 401-416, 1991.

NETWORK PROPAGATION:

Gordon, J., and Shortliffe, E. H., A Method for Managing Evidential
Reasoning in a Hierarchical Hypothesis Space, Artif. Intell. 26(3),
323-357, 1985.

Shafer, G., and Logan, R., Implementing Dempster's Rule for
Hierarchical Evidence, Artif. Intell. 33(3), 271-298, 1987.

DECISION MAKING:

Nguyen, H. T., and Walker, E. A., On decision making using belief
functions, in Advances in the Dempster-Shafer Theory of Evidence
(R. Y. Yager, M. Fedrizzi and J. Kacprzyk, Eds.), John Wiley & Sons,
Inc., New York, 311-330, 1994.

Smets, P., and Kennes, R., The transferable belief model,
Artif. Intell. 66(2), 191-234, 1994.

CLUSTERING:

Schubert, J., Cluster-Based Specification Techniques in
Dempster-Shafer Theory,in Symbolic and Quantitative Approaches to
Reasoning and Uncertainty (C. Froidevaux and J. Kohlas, Eds.),
Springer-Verlag (LNAI 946), Berlin, 395-404, 1995.

Denoeux, T., A k-nearest neighbor classification rule based on
Dempster-Shafer theory, IEEE Trans. Syst. Man Cyber. 25(5), 804-813,
1995.

EXPLANING RESULTS:

Strat, T. M., and Lowrance, J. D., Explaining Evidential Analyses,
Int. J. Approx. Reasoning 3(4), 299-353, 1989.

SYSTEMS:

Xu, H., An Efficient Tool for Reasoning with Belief Functions,
Proceedings of the 4th International Conference on Information
Processing and Management of Uncertainty, Mallorca, 65-68, 1992.

Zarley, D., Hsia, Y.-T., and Shafer, G., Evidential Reasoning Using
DELIEF, Proceedings of the 7th National Conference on AI, Saint Paul,
Minn., 205-209, 1988.

Lowrance, J. D., Garvey, T. D., and Strat, T. M., A framework for
evidential-reasoning systems, Proceedings of the 5th National
Conference on AI, Philadelphia, Penn., 896-901, 1986.

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Enjoy!

Johan Schubert