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Explainable AI and Other Applications of Fuzzy Techniques: Proceedings the 2021 Annual Conference North American Information Processing Society, NAFIPSExplainable AI and Other Applications of Fuzzy Techniques: Proceedings the 2021 Annual Conference North American Information Processing Society, NAFIPS

Explainable AI and Other Applications of Fuzzy Techniques: Proceedings the 2021 Annual Conference North American Information Processing Society, NAFIPS in Ottawa, ON

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Current price: $308.39
Original price: $385.42
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Explainable AI and Other Applications of Fuzzy Techniques: Proceedings the 2021 Annual Conference North American Information Processing Society, NAFIPS

By None

Explainable AI and Other Applications of Fuzzy Techniques: Proceedings the 2021 Annual Conference North American Information Processing Society, NAFIPS in Ottawa, ON

Current price: $308.39
Original price: $385.42
Loading Inventory...

Size: Kobo eBook

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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.
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.

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