Fril, Fuzzy and Evidential Reasoning in Artificial Intelligence (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence)

PDF-file by J.F. Baldwin

Fril, Fuzzy and Evidential Reasoning in Artificial Intelligence (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence) PDF ebook download The knowledge engineer requires modelling paradigms and associative inference methods that can be used for software development of practical applications. This book presents a theory of uncertainty relevant to knowledge engineering that is consistent with, and brings together, the theories of probability and fuzzy sets. It extends the logic programming form of knowledge representation and method of inference to allow the inclusion of uncertainties such as probabilistic knowledge and fuzzy incompleteness. It describes the application to general areas of knowledge engineering such as expert and decision-support systems, evidential and case-based reasoning, fuzzy control and fuzzy databases. Fril, the artificial intelligence language that implements this theory of uncertainty in the style of logic programming, is presented, with many examples and modules for the various applications. Two Fril demonstration disks are provided free in the book, one for the Macintosh computer and one for the IBM PC, so that the reader can implement these examples while following the text.

eBook Fril, Fuzzy and Evidential Reasoning in Artificial Intelligence (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence, 1) (Uncertainty Theory in Artificial Intelligence)

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