Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

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  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 6
    Truth Ratios of Syllogistic Moods
    (Institute of Electrical and Electronics Engineers, 2015) Zarechnev, Mikhail; Kumova, Bora İsmail
    The syllogistic system consists of 256 moods, of which only 24 have been recognized as true. From a set-theoretical point of view, a mood can be represented with three sets and their possible relationships. Three sets can have up to seven sub-sets or spaces. In an earlier work we have used 41 permutations of the spaces, out of which every mood matches an individual number as true or false cases. The truth ratio of a mood is then calculated, by relating the true and false cases with each other. In this work we revise the previously presented properties of the moods and the syllogistic system, this time by using the maximum possible cover, which consists of 96 distinct space permutations. Our results mostly verify our previous findings, like the additional true mood anasoy, the inherently symmetric truth distribution of the moods. Additionally we have revealed some new properties, like the equivalence of some moods, which reduces the system to 136 distinct moods.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 2
    An Extended Syllogistic Logic for Automated Reasoning
    (Institute of Electrical and Electronics Engineers, 2017) Çine, Ersin; Kumova, Bora İsmail
    In this work, we generalise the categorical syllogistic logic in several dimensions to a relatively expressive logic that is sufficiently powerful to encompass a wider range of linguistic semantics. The generalisation is necessary in order to eliminate the existential ambiguity of the quantifiers and to increase expressiveness, practicality, and adaptivity of the syllogisms. The extended semantics is expressed in an extended syntax such that an algorithmic solution of the extended syllogisms can be processed. Our algorithmic approach for deduction in this logic allows for automated reasoning directly with quantified propositions, without reduction of quantifiers.
  • Conference Object
    Syllogistic Knowledge Bases With Description Logic Reasoners
    (IEEE, 2018) Çine, Ersin
    Reasoning is a core topic both for natural intelligence and for artificial intelligence. While syllogistic logics (SLs) are often studied by cognitive scientists for understanding human reasoning, description logics (DLs) are usually studied by computer scientists for performing automated reasoning. Although the studies on both of these logics are extensive, their literatures are interestingly isolated from each other. Firstly, we formally define a practical family of SLs with different levels of expressivity, including a logic which has recently been introduced for automated reasoning. Then, we reveal their theoretical properties either by defining direct algorithms for deductive reasoning or by translation rules for them into relevant DLs. These algorithms and rules prove that (i) two of our SLs (namely PolSyl and NegSyl) are tractable fragments of DLs, and (ii) other two SLs (namely ComSyl and ComSyl+) are categorical fragments of DL AEC and DL AEC:0 with general TBoxes, respectively. These findings bridge the gap between (ancient) SLs and (modern) DLs. An immediate result is that it is possible to combine powerful features of both logics, for example, intuitional user interface of an SL and efficient reasoning algorithms for a DL. Finally, we propose a framework for knowledge representation in SLs and link it to sound and complete DL reasoners for automated deduction.