Inhaltsangabe
How to read evidence and beliefs as a shared vote among experts. This primer explains a way to view the Dempster/Shafer theory of evidence as statistics of expert opinions, using Bayes’ updating to connect belief values with probabilities. It introduces belief, plausibility, and commonality, and shows how a simple, trackable set of numbers can summarize complex uncertainty. Read this edition to see how a theory of evidence maps to a practical, Bayesian viewpoint.
The book argues that combining evidence can be seen as updating probabilities over the product space of experts. It compares the traditional mass-based approach with an alternative that keeps probabilistic (logarithmic) opinions, offering a simpler computational path. By tying the ideas to what experts think, the text clarifies the foundations and the trade‑offs involved in modeling uncertainty.
- Learn how belief and plausibility relate to lower and upper probabilities in a concrete way.
- See how combining pieces of evidence mirrors Bayesian updates on labeled possibilities.
- Explore a streamlined formulation that reduces the number of parameters while tracking expert opinions.
- Understand differences between ambiguous knowledge and uncertain knowledge through opinion distributions.
Ideal for readers of statistics, decision theory, and knowledge engineering who want a clear, applied perspective on the theory of evidence.
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A Statistical Viewpoint on the Theory of Evidence (Classic Reprint)
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Paperback. Zustand: New. Print on Demand. This book offers a novel viewpoint on the Dempster/Shafer Theory of Evidence, a notable framework for reasoning with uncertainty. The author argues that the theory can be understood as a form of statistical analysis of expert opinions. This perspective simplifies the interpretation of the theory's core combination formulas, revealing that they represent Bayesian updating applied to boolean assertions. The book also proposes an alternative formulation that employs probabilistic opinions of experts, leading to simpler formulas and fewer variables while maintaining the essential idea of tracking expert opinion statistics. The combination formula, rather than extending Bayes' theorem for combining probabilities, contains nothing more than Bayes' formula applied to boolean assertions. By treating the formulation as algebraic structures, and by treating opinions as the Statistics on a collection of opinions, the book provides canonical examples with which to construct states of belief to analogous real situations. This approach provides a deeper theoretical basis for the application of canonical examples to probabilistic situations with uncertainties. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Bestandsnummer des Verkäufers 9781333644703_0
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A Statistical Viewpoint on the Theory of Evidence Classic Reprint
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A Statistical Viewpoint on the Theory of Evidence Classic Reprint
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