Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6777
Title: The fuzzy syllogistic system
Authors: Kumova, Bora İsmail
Çakır, Hüseyin
Keywords: Approximate reasoning
Automated reasoning
Syllogistic reasoning
Fallacies
Issue Date: 2010
Publisher: Springer Verlag
Source: Kumova, B. İ., and Çakır, H. (2010). The fuzzy syllogistic system. Lecture Notes in Computer Science, 6438 LNAI (PART 2), 418-427. doi:10.1007/978-3-642-16773-7_36
Abstract: A categorical syllogism is a rule of inference, consisting of two premisses and one conclusion. Every premiss and conclusion consists of dual relationships between the objects M, P, S. Logicians usually use only true syllogisms for deductive reasoning. After predicate logic had superseded syllogisms in the 19th century, interest on the syllogistic system vanished. We have analysed the syllogistic system, which consists of 256 syllogistic moods in total, algorithmically. We have discovered that the symmetric structure of syllogistic figure formation is inherited to the moods and their truth values, making the syllogistic system an inherently symmetric reasoning mechanism, consisting of 25 true, 100 unlikely, 6 uncertain, 100 likely and 25 false moods. In this contribution, we discuss the most significant statistical properties of the syllogistic system and define on top of that the fuzzy syllogistic system. The fuzzy syllogistic system allows for syllogistic approximate reasoning inductively learned M, P, S relationships.
Description: 9th Mexican International Conference on Artificial Intelligence, MICAI 2010; Pachuca; Mexico; 8 November 2010 through 13 November 2010
URI: http://doi.org/10.1007/978-3-642-16773-7_36
http://hdl.handle.net/11147/6777
ISBN: 9783642167720
ISSN: 0302-9743
1611-3349
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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