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Syllogism is a type of deductive reasoning involving quantified statements. The syllogistic reasoning scheme in the classical Aristotelian framework involves three crisp term sets and four linguistic quantifiers, for which the main support…

Artificial Intelligence · Computer Science 2014-12-01 M. Pereira-Fariña , F. Díaz-Hermida , A. Bugarín

Deep learning (DL) libraries, widely used in AI applications, often contain vulnerabilities like buffer overflows and use-after-free errors. Traditional fuzzing struggles with the complexity and API diversity of DL libraries such as…

Software Engineering · Computer Science 2025-01-09 Kunpeng Zhang , Shuai Wang , Jitao Han , Xiaogang Zhu , Xian Li , Shaohua Wang , Sheng Wen

Logic programming, as exemplified by datalog, defines the meaning of a program as its unique smallest model: the deductive closure of its inference rules. However, many problems call for an enumeration of models that vary along some set of…

Programming Languages · Computer Science 2024-11-22 Chris Martens , Robert J. Simmons , Michael Arntzenius

Answer set programming is one of the most praised frameworks for declarative programming in general and non-monotonic reasoning in particular. There has been many efforts to extend stable model semantics so that answer set programs can use…

Logic in Computer Science · Computer Science 2012-12-04 Shahab Tasharrofi

Practically all programming languages allow the programmer to split a program into several modules which brings along several advantages in software development. In this paper, we are interested in the area of answer-set programming where…

Logic in Computer Science · Computer Science 2014-01-16 Tomi Janhunen , Emilia Oikarinen , Hans Tompits , Stefan Woltran

Answer Set Programming (ASP) is a declarative programming paradigm based on logic programming and non-monotonic reasoning. It is a tremendously powerful tool for describing and solving combinatorial problems. Like any other language, ASP…

Artificial Intelligence · Computer Science 2025-11-13 Connar Hite , Sean Saud , Raef Taha , Nayim Rahman , Tanvir Atahary , Scott Douglass , Tarek Taha

The treatment of complex systems often requires the manipulation of vague, imprecise and uncertain information. Indeed, the human being is competent in handling of such systems in a natural way. Instead of thinking in mathematical terms,…

Artificial Intelligence · Computer Science 2013-11-20 Baghdad Atmani , Sofia Benbelkacem , Mohamed Benamina

In this paper we introduce a fuzzy constraint linear discriminant analysis (FC-LDA). The FC-LDA tries to minimize misclassification error based on modified perceptron criterion that benefits handling the uncertainty near the decision…

Artificial Intelligence · Computer Science 2017-01-02 Hamid Reza Hassanzadeh , Hadi Sadoghi Yazdi , Abedin Vahedian

This paper proposes the meeting of fuzzy logic with paraconsistency in a very precise and foundational way. Specifically, in this paper we introduce expansions of the fuzzy logic MTL by means of primitive operators for consistency and…

Logic · Mathematics 2021-03-15 Marcelo Coniglio , Francesc Esteva , Lluís Godo

Prediction sets offer a binary inclusion/exclusion for each element at the same fixed confidence level. We generalize to fuzzy prediction sets, which exclude elements at their own data-driven confidence level. Our key insight is that a…

Statistics Theory · Mathematics 2026-04-01 Nick W. Koning , Sam van Meer

Security vulnerabilities in Internet-of-Things devices, mobile platforms, and autonomous systems remain critical. Traditional mutation-based fuzzers -- while effectively explore code paths -- primarily perform byte- or bit-level edits…

Software Engineering · Computer Science 2025-09-25 Mengdi Lu , Steven Ding , Furkan Alaca , Philippe Charland

A relational database is inconsistent if it does not satisfy a given set of integrity constraints. Nevertheless, it is likely that most of the data in it is consistent with the constraints. In this paper we apply logic programming based on…

Databases · Computer Science 2007-05-23 Marcelo Arenas , Leopoldo Bertossi , Jan Chomicki

Hesitant fuzzy sets find extensive application in specific scenarios involving uncertainty and hesitation. In the context of set theory, the concept of inclusion relationship holds significant importance as a fundamental definition.…

Artificial Intelligence · Computer Science 2025-04-21 Shizhan Lu , Zeshui Xu , Zhu Fu , Longsheng Cheng , Tongbin Yang

In this paper we present a short survey of fuzzy and Semantic approaches to Knowledge Extraction. The goal of such approaches is to define flexible Knowledge Extraction Systems able to deal with the inherent vagueness and uncertainty of the…

Information Retrieval · Computer Science 2013-01-25 Mohamed Nazih Omri

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not…

Artificial Intelligence · Computer Science 2012-03-19 Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir

Flexible querying of DB allows to extend DBMS in order to support imprecision and flexibility in queries. Flexible queries use vague and imprecise terms which have been defined as fuzzy sets. However, there is no consensus on memberships…

Databases · Computer Science 2020-05-11 Narjes Hachani Gharbi

In this paper, we propose a variant of stable model semantics for disjunctive logic programming and deductive databases. The semantics, called minimal founded, generalizes stable model semantics for normal (i.e. non disjunctive) programs…

Logic in Computer Science · Computer Science 2007-05-23 Filippo Furfaro , Gianluigi Greco , Sergio Greco

WordNet lexical-database groups English words into sets of synonyms called "synsets." Synsets are utilized for several applications in the field of text-mining. However, they were also open to criticism because although, in reality, not all…

Prioritized default reasoning has illustrated its rich expressiveness and flexibility in knowledge representation and reasoning. However, many important aspects of prioritized default reasoning have yet to be thoroughly explored. In this…

Artificial Intelligence · Computer Science 2007-05-23 Yan Zhang

We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and…

Artificial Intelligence · Computer Science 2016-11-17 Tomoyuki Yamakami