Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques e-bog
436,85 DKK
(inkl. moms 546,06 DKK)
Modern AI techniques -- especially deep learning -- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to p...
E-bog
436,85 DKK
Forlag
Springer
Udgivet
16 september 2022
Genrer
Databases
Sprog
English
Format
pdf
Beskyttelse
LCP
ISBN
9783031099748
Modern AI techniques -- especially deep learning -- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "e;small"e; -- into control and decision making. For this incorporation, a special "e;fuzzy"e; technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.