Handling Uncertainty in Artificial Intelligence - Chaki, Jyotismita
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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.…mehr

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Produktbeschreibung
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.

Autorenporträt
Dr. Jyotismita Chaki is an Associate Professor at the School of Computer Science and Engineering, Vellore Institute of Technology, India. She holds a Ph.D. in Engineering from Jadavpur University, Kolkata, and her research interests encompass Computer Vision, Image Processing, Pattern Recognition, Medical Imaging, Artificial Intelligence, and Machine Learning. Dr. Chaki is an author and editor, with a substantial body of work including five authored books published by renowned presses like Springer and CRC Press, and six edited books published by CRC Press and Elsevier. She has also published many research articles in high-impact, SCIE-indexed journals, the majority of which are ranked in the top quartiles (Q1 and Q2). In recognition of her contributions, Dr. Chaki was named the world's top 2% scientist by Stanford University and Elsevier in 2024. She is also a Senior Member of the IEEE. Dr. Chaki's editorial contributions are extensive, currently serving as editor for 9 journals, including Engineering Applications of Artificial Intelligence (Elsevier), Scientific Reports (Nature Portfolio), Discover Applied Sciences (Springer Nature), PLOS ONE, PeerJ Computer Science, Computer and Electrical Engineering (Elsevier), Array (Elsevier), Machine Learning with Applications (Elsevier), and BMC Artificial Intelligence.