Interpretable Artificial Intelligence: A Perspective of Granular Computing: 937 1st ed. 2021 Edition

Interpretable Artificial Intelligence: A Perspective of Granular Computing: 937 1st ed. 2021 Edition book cover

Interpretable Artificial Intelligence: A Perspective of Granular Computing: 937 1st ed. 2021 Edition

Author(s): Witold Pedrycz (Editor), Shyi-Ming Chen

  • Publisher: Springer
  • Publication Date: 29 Mar. 2022
  • Edition: 1st ed. 2021
  • Language: English
  • Print length: 437 pages
  • ISBN-10: 3030649512
  • ISBN-13: 9783030649517

Book Description

This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.

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From the Back Cover

This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.

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