Fuzzy Systems, Soft Computing, and Explainable AI
暫譯: 模糊系統、軟體計算與可解釋 AI

This book is about techniques that can make AI more explainable.
While AI techniques have been spectacularly successful, they are not perfect: their answers are often wrong. To distinguish between great and flawed recommendations, it is desirable to make AI systems explain their recommendations.
This means translating numerical computations--that AI systems perform--into human-understandable natural-language form. It thus makes sense to use existing techniques--e.g., fuzzy--that connect numerical computations with natural language.
The use of fuzzy techniques to make AI explainable is the book's focus. This book contains both theoretical results and applications--to aerospace engineering, agriculture, biology, digital twins, education, law enforcement, medicine, etc. It can be recommended to students and practitioners interested in the state-of-the-art fuzzy-related explainable AI, and to researchers focused on remaining challenges.