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Dempster-Shafer Theory

Dempster-Shafer theory is a mathematical framework for reasoning under uncertainty that generalizes Bayesian probability by representing ignorance explicitly. Instead of forcing a single probability on each hypothesis, it assigns belief mass to sets of hypotheses and derives a belief-plausibility interval, and it provides Dempster's rule for fusing evidence from multiple independent sources. Developed from Arthur Dempster's 1967 work and Glenn Shafer's 1976 monograph, it underpins evidential reasoning and sensor/decision fusion.

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Dempster-Shafer Theory of Evidence (Belief Functions)

Rekodi ya mbinu ya kiajenda · ml-model / soft-computing

Dempster, A. P. (1967). Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38(2), 325–339. · DOI 10.1214/aoms/1177698950
Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton University Press. · ISBN 978-0-691-08175-5

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