Explainable Ai and Other Applications of Fuzzy Techniques : Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, Nafips 2021
Language: English
Published by Springer, 2021
Series: Book 256 of 391 - Lecture Notes in Networks and Systems
- Softcover
- Used

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- Title
- Explainable Ai and Other Applications of Fuzzy Techniques : Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, Nafips 2021
- Author
- Rayz, Julia (EDT); Raskin, Victor (EDT); Dick, Scott (EDT); Kreinovich, Vladik (EDT)
- Publisher
- Springer
- Publication year
- 2021
- Condition
- As New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 303082098X
- ISBN 13
- 9783030820985
- Series
- Book 256 of 391: Lecture Notes in Networks and Systems
This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques.
This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general."Synopsis" may belong to another edition of this title.
From the Back Cover
This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques.
This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI―in short, to anyone who is interested in problems involving fuzziness and AI in general.
"About the title" may belong to another edition of this title.
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