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Handling Uncertainty in Artificial Intelligence

Handling Uncertainty in Artificial Intelligence

Jyotismita Chaki

Springer Nature

Cheaper in another edition — £35.99 at Springer Nature Link Shop Handling Uncertainty in Artificial Intelligence · See that edition →

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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