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Probabilistic Expert Systems (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 67) by Glenn Shafer is a nonfiction available to read on EtoBox.

What is Probabilistic Expert Systems (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 67) about?

Probabilistic Expert Systems emphasizes the basic computational principles that make probabilistic reasoning feasible in expert systems. The key to computation in these systems is the modularity of the probabilistic model. Shafer describes and compares the principal architectures for exploiting this modularity in the computation of prior and posterior probabilities. He also indicates how these similar yet different architectures apply to a wide variety of other problems of recursive computation in applied mathematics and operations research. The field of probabilistic expert systems has continued to flourish since the author delivered his lectures on the topic in June 1992, but the understanding of join-tree architectures has remained missing from the literature. This monograph fills this void by providing an analysis of join-tree methods for the computation of prior and posterior probabilities in belief nets. These methods, pioneered in the mid to late 1980s, continue to be central to the theory and practice of probabilistic expert systems. In addition to purely probabilistic expert systems, join-tree methods are also used in expert systems based on Dempster–Shafer belief fun

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Author

Glenn Shafer

Publisher

Society For Industrial And Applied Mathematics

Published

1987

Language

EN

ISBN

9780898713732

Category

nonfiction

Subjects

Computer Science, Mathematics, Science