The Fuzzy Syllogistic System

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Date

2010

Authors

Kumova, Bora İsmail

Journal Title

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Publisher

Springer Verlag

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Green Open Access

Yes

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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 After predicate logic had superseded syllogisms in the 19th century, interest on the syllogistic system vanished.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

Keywords

Approximate reasoning, Automated reasoning, Syllogistic reasoning, Fallacies, Automated reasoning, Fallacies, Approximate reasoning, Syllogistic reasoning

Fields of Science

03 medical and health sciences, 0302 clinical medicine, 05 social sciences, 0501 psychology and cognitive sciences

Citation

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

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N/A

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Q3
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OpenCitations Citation Count
6

Source

Lecture Notes in Computer Science

Volume

6438 LNAI

Issue

PART 2

Start Page

418

End Page

427
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CrossRef : 5

Scopus : 8

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Mendeley Readers : 1

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8

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5

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Page Views

1376

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Downloads

647

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