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| Title: | Axioms for Probability and Belief-Function Propagation |
| Authors: | Shenoy, Prakash P.
Shafer, Glenn |
| Keywords: | Axioms
local computation
probability
Dempster-Shafer belief function theory |
| Issue Date: | 1990 |
| Publisher: | Elsevier Science Publishers B. V. |
| Extent: | 239375 bytes |
| Type: | Book chapter |
| Citation: | In R. D. Shachter, T. S. Levitt, L. N. Kanal and J. F. Lemmer (eds.), Uncertainty in Artificial Intelligence 4, 1990, 169--198, North-Holland, Amsterdam. |
| Series/Report no.: | Machine Intelligence and Pattern Recognition;Volume 9 |
| Abstract: | In this paper, we describe an abstract framework and axioms under which exact local computation of marginals is possible. The primitive objects of the framework are variables and valuations. The
primitive operators of the framework are combination and marginalization. These operate on valuations. We state three axioms for these operators and we derive the possibility of local computation from the axioms. Next, we describe a propagation scheme for computing marginals of a valuation when we have a factorization of the valuation on a hypertree. Finally we show how the problem of computing marginals of joint probability distributions and joint belief functions fits the general framework |
| Description: | This article was reprinted in G. Shafer and J. Pearl (eds.), Readings in Uncertain Reasoning, 1990, pp. 575-610, Morgan Kaufmann, San Mateo, CA. Also, a condensed 8-pp version of this paper appeared in the Proceedings of the Fourth Workshop on Uncertainty in Artificial Intelligence in 1988. |
| URI: | http://hdl.handle.net/1808/144 |
| ISBN: | 0 444 88650 8 |
| Appears in Collections: | School of Business Articles
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