Interpretable Artificial Intelligence: A Perspective of Granular Computing

Shyi-Ming Chen

ISBN 10: 3030649512 / ISBN 13: 9783030649517

Published by Springer International Publishing, 2022

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783030649517

Bibliographic Details

• Title: Interpretable Artificial Intelligence: A Perspective of Granular Computing
• Publisher: Springer International Publishing
• Publication Date: 2022
• Language: English
• ISBN 10: 3030649512
• ISBN 13: 9783030649517
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 24D millimeters 235 millimeters width by 155 millimeters height by 24 millimeters depth
• Weight: 663 grams

About this title

Synopsis

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.