Download Classic Works of the Dempster-Shafer Theory of Belief by Ronald R. Yager, Liping Liu PDF

By Ronald R. Yager, Liping Liu

This e-book brings jointly a suite of vintage examine papers at the Dempster-Shafer concept of trust capabilities. through bridging fuzzy common sense and probabilistic reasoning, the idea of trust services has turn into a main device for wisdom illustration and uncertainty reasoning in specialist platforms. This publication will function the authoritative reference within the box of evidential reasoning and a big archival reference in quite a lot of components together with uncertainty reasoning in man made intelligence and determination making in economics, engineering, and administration. From over a hundred and twenty nominated contributions, the editors chosen 30 papers, that are largely considered as classics and should proceed to make affects at the destiny improvement of the sector. The contributions are grouped into seven sections, together with conceptual foundations, theoretical views, theoretical extensions, replacement interpretations, and functions to synthetic intelligence, decision-making, and statistical inferences. The booklet additionally incorporates a foreword via Dempster and Shafer reflecting the improvement of the speculation within the final 40 years, and an creation describing the elemental parts of the speculation and the way each one paper contributes to the sphere.

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Extra resources for Classic Works of the Dempster-Shafer Theory of Belief Functions

Sample text

The concept of pivotal variables was highly confusing, restrictive, and controversial [7]. Dempster devoted much of his early research career at Harvard to clarifying, extending, and perfecting the method. For example, he once proposed the concept of direct probabilities as his interpretation of the fiducial argument [5]. First, to make the derivation of fiducial probabilities explicit, he introduced an arbitrary function v = V (x) so that it along with (16) implied a smooth one-to-one function from x and θ to u and v, and therefore ensured the existence of the following Jacobian: ∂(u, v) .

These concepts served two purposes. First, they showed how weights of evidence might be converted into degrees of belief and combined using Dempster’s rule, and thus showed how the theory of belief functions could be rebuilt and applied around these concepts. Second, they justified the theory of belief functions from works of Jakob Bernoulli and other ancient scholars on probabilities. It was probably from these works Shafer generated his idea of re-interpreting Dempster’s work as a theory of probable reasoning through the combination of evidence.

The logical foundations of evidential reasoning. Tech. , SRI International, Menlo Park, California, 1986. [32] Savage, L. J. The Foundations of Statistics. Wiley, New York, NY, 1954. [33] Schapire, R. E. The strength of weak learnability. Machine Learning 5 (1990), 197–227. [34] Shafer, G. A Mathematical Theory of Evidence.

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