Handling Uncertainty in Artificial Intelligence

Jyotismita Chaki

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ca. 48,14

Springer Nature Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Allgemeines, Lexika

Beschreibung

This book demonstrates different methods (as well as real-life examples) of handling uncertainty like probability and Bayesian theory, Dempster-Shafer theory, certainty factor and evidential reasoning, fuzzy logic-based approach, utility theory and expected utility theory. At the end, highlights will be on the use of these methods which can help to make decisions under uncertain situations. This book assists scholars and students who might like to learn about this area as well as others who may have begun without a formal presentation. The book is comprehensive, but it prohibits unnecessary mathematics.

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Schlagwörter

Dempster-Shafer Theory, Certainty factor and evidential reasoning, Cohen's theory of endorsements, Fuzzy logic-based approach, Decision making, Nonmonotonic approaches