The importance of Trustworthy and Explainable Artificial Intelligence (XAI) is recognized in academia, industry and society. This book introduces tools for dealing with imprecision and uncertainty in XAI applications where explanations are demanded, mainly in natural language.
Design of Explainable Fuzzy Systems (EXFS) is rooted in Interpretable Fuzzy Systems, which are thoroughly covered in the book. The idea of interpretability in fuzzy systems, which is grounded on mathematical constraints and assessment functions, is firstly introduced. Then, design methodologies are described. Finally, the book shows with practical examples how to design EXFS from interpretable fuzzy systems and natural language generation. This approach is supported by open source software.
The book is intended for researchers, students and practitioners who wish to explore EXFS from theoretical and practical viewpoints. The breadth of coverage will inspire novel applications and scientific advancements.
Explains in details how fuzzy models can participate in the construction of decision systems
This remarkable book establishes a bridge with natural language processing and automatic text generation and it proposes solutions to deal with the well-known interpretability-accuracy trade-off
Covers all aspects of interpretability of fuzzy rule-based systems, from interpretability rating to directly exploitable software
It paves the way for a greater involvement of fuzzy methods in Explainable Artificial Intelligence