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Why Not Fuzzy Logic?
U: Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives / Skansi, Sandro (ur.). Cham: Springer Nature Switzerland AG, 2020. str. 29-40. urn:nbn:hr:261:520402
Restović, Ivan

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Restović, I. (2020). Why Not Fuzzy Logic?. U S. Skansi, (Ur.), Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives (str. 29-40). Cham: Springer Nature Switzerland AG. Preuzeto s https://urn.nsk.hr/urn:nbn:hr:261:520402

Restović, Ivan. "Why Not Fuzzy Logic?." Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives, Ur. Sandro Skansi, Springer Nature Switzerland AG, 2020, str. 29-40. https://urn.nsk.hr/urn:nbn:hr:261:520402

Restović, Ivan. "Why Not Fuzzy Logic?." U Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives, ur. Sandro Skansi, 29-40. Cham: Springer Nature Switzerland AG, 2020. https://urn.nsk.hr/urn:nbn:hr:261:520402

Restović, I. (2020) 'Why Not Fuzzy Logic?' u Skansi, S. (ur.) Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives Cham: Springer Nature Switzerland AG, str. 29-40. Preuzeto s: https://urn.nsk.hr/urn:nbn:hr:261:520402 (Datum pristupa: 09.12.2024.)

Restović I. Why Not Fuzzy Logic?. U: S. Skansi, ur. Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives. Cham: Springer Nature Switzerland AG; 2020. Str. 29-40. [pristupljeno 09.12.2024.] Dostupno na: https://urn.nsk.hr/urn:nbn:hr:261:520402

I. Restović, "Why Not Fuzzy Logic?", Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives, S. Skansi, Ur. Cham: Springer Nature Switzerland AG, 2020, str. 29-40. [Online] Dostupno na: https://urn.nsk.hr/urn:nbn:hr:261:520402

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Podaci o radu
Naslov (engleski)Why Not Fuzzy Logic?
AutorIvan Restović
UrednikSandro Skansi
Autorova ustanovaInstitut za filozofiju
Znanstveno / umjetničko
područje, polje i grana		HUMANISTIČKE ZNANOSTI
Filozofija
Logika
Sažetak (engleski)
Fuzzy logic is an approach to AI which focuses on the mechanization of natural language. It has long been proposed by Zadeh, its originator, as another paradigm for AI and the correct way to achieve "human level machine intelligence". To present day, this approach hasn't prevailed, but in the light of some recent tendencies in AI development it can gain traction. The "black-box property" of the currently predominant method — deep learning — has recently sparked a movement called "explainable artificial intelligence", a quest for AI that can explain its decisions in a way understandable and acceptable to humans. As it has been recognized, a natural way to provide explanations to users is to use natural language, embedded in the fuzzy logic paradigm. However, to model natural language fuzzy logic uses the notion of "partial truth", which has brought some philosophical concerns. The very core tenets of fuzzy logic have often been described as counterintuitive. In this text, we provide philosophical support for fuzzy logic by providing possible answers to the two most common critiques raised about it, as well as by offering independent philosophical motivation for endorsing it.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Poglavlje u knjizi
Status objaveObjavljen
Vrsta recenzijeRecenziran
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov knjigeGuide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives
Brojčani podacistr. 29-40
ISBN978-3-030-37590-4
URN:NBNurn:nbn:hr:261:520402
Datum objave publikacije2020
Vrsta resursaTekst
IzdavačSpringer Nature Switzerland AG
Mjesto izdavanjaCham
Prava pristupaZatvoreni pristup
Uvjeti korištenjaIkona licence Zaštićeno autorskim pravom.
Datum i vrijeme pohrane2022-10-17 14:19:27