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010   $a9783031099748$b(electronic bk.)
010   $z9783031099731
024 7 $a10.1007/978-3-031-09974-8
035   $a(MiAaPQ)EBC7088329
035   $a(Au-PeEL)EBL7088329
035   $a(CKB)24846073300041
035   $a(DE-He213)978-3-031-09974-8
035   $a(PPN)264953746
035   $a(EXLCZ)9924846073300041
100   $a20220916d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aTowards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques /$fby Vladik Kreinovich
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (136 pages)
225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v1047
311 08$aPrint version: Kreinovich, Vladik Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques Cham : Springer International Publishing AG,c2022 9783031099731 
320   $aIncludes bibliographical references and index.
327   $aWhy Explainable AI? Why Fuzzy Explainable AI? What Is Fuzzy? -- Defuzzification -- Which Fuzzy Techniques? -- So How Can We Design Explainable Fuzzy AI: Ideas -- How to Make Machine Learning Itself More Explainable -- Final Self-Test.
330   $aModern AI techniques ?- especially deep learning ?- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "small" -- into control and decision making. For this incorporation, a special "fuzzy" technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.
410  0$aStudies in Computational Intelligence,$x1860-9503 ;$v1047
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aEngineering$xData processing
606   $aComputational Intelligence
606   $aArtificial Intelligence
606   $aData Engineering
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aEngineering$xData processing.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aData Engineering.
676   $a006.3
676   $a006.3
700   $aKreinovich$b Vladik $0117742
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910595058303321
996   $aTowards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques$93577400
997   $aUNINA