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Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques: 1047 (Studies in Computational Intelligence) - Tapa blanda

Kreinovich, Vladik

 
9783031099762: Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques: 1047 (Studies in Computational Intelligence)
Tapa blanda
ISBN 10: 3031099761 ISBN 13: 9783031099762
Editorial: Springer, 2023

Sinopsis

Modern AI techniques –- especially deep learning –- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "small" -- into control and decision making. For this incorporation, a special "fuzzy" technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.

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Acerca del autor

Vladik Kreinovich is Professor of Computer Science at the University of Texas at El Paso. His main interests computations and intelligent control. He has published 13 books, 39 edited books, and more than 1,800 papers.


Vladik is Vice President of the International Fuzzy Systems Association (IFSA), Vice President of the European Society for Fuzzy Logic and Technology (EUSFLAT), Fellow of International Fuzzy Systems Association (IFSA), Fellow of Mexican Society for Artificial Intelligence (SMIA), Fellow of the Russian Association for Fuzzy Systems and Soft Computing. He is Treasurer of IEEE Systems, Man, and Cybernetics Society

De la contraportada

Modern AI techniques –- especially deep learning –- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "small" -- into control and decision making. For this incorporation, a special "fuzzy" technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2023
Idioma
Inglés
ISBN 10 
3031099761
ISBN 13 
9783031099762
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
142
Contacto del fabricante
no disponible
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