| 书目名称 | Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques | | 编辑 | Vladik Kreinovich | | 视频video | | | 概述 | Presents concepts, paradigms, tools, and techniques for Explainable Fuzzy AI.Presents fuzzy approaches to explainable AI.Graduate Textbook even understandable for undergraduate students | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | 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 "small" -- into control and decision making. For this incorporation, a special "fuzzy" 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.. | | 出版日期 | Textbook 2022 | | 关键词 | Computational Intelligence; AI; Explainable AI; Fuzzy Techniques; Explainable Fuzzy AI | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-09974-8 | | isbn_softcover | 978-3-031-09976-2 | | isbn_ebook | 978-3-031-09974-8Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:56:50
