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Related papers: Fuzzy Time in LTL

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A predicate linear temporal logic LTL_{\lambda,=} without quantifiers but with predicate abstraction mechanism and equality is considered. The models of LTL_{\lambda,=} can be naturally seen as the systems of pebbles (flexible constants)…

Logic in Computer Science · Computer Science 2007-05-23 Alexei Lisitsa , Igor Potapov

Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts. However, the ability of current large language models (LLMs) to handle such reasoning remains largely uncharted. In this paper, we introduce a new…

Artificial Intelligence · Computer Science 2024-07-04 Yiyuan Li , Shichao Sun , Pengfei Liu

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

Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited…

Logic in Computer Science · Computer Science 2021-04-30 Daniel Neider , Alexander Weinert , Martin Zimmermann

Fuzzy logic programming is a growing declarative paradigm aiming to integrate fuzzy logic into logic programming. One of the most difficult tasks when specifying a fuzzy logic program is determining the right weights for each rule, as well…

Programming Languages · Computer Science 2016-08-17 Ginés Moreno , Jaime Penabad , Germán Vidal

Fuzzy discrete event systems as a generalization of (crisp) discrete event systems have been introduced in order that it is possible to effectively represent uncertainty, imprecision, and vagueness arising from the dynamic of systems. A…

Discrete Mathematics · Computer Science 2007-05-23 Yongzhi Cao , Mingsheng Ying

Risk specialists are trying to understand risk better and use complex models for risk assessment, while many risks are not yet well understood. The lack of empirical data and complex causal and outcome relationships make it difficult to…

Artificial Intelligence · Computer Science 2020-09-22 Hengameh Fakhravar

The paper introduces fuzzy linguistic logic programming, which is a combination of fuzzy logic programming, introduced by P. Vojtas, and hedge algebras in order to facilitate the representation and reasoning on human knowledge expressed in…

Logic in Computer Science · Computer Science 2009-04-06 Van Hung Le , Fei Liu , Dinh Khang Tran

This paper shows that the fuzzy temporal logic can model figures of thought to describe decision-making behaviors. In order to exemplify, some economic behaviors observed experimentally were modeled from problems of choice containing time,…

Artificial Intelligence · Computer Science 2019-02-18 José Cláudio do Nascimento

The problem of checking a logged event trace against a temporal logic specification arises in many practical cases. Unfortunately, known algorithms for an expressive logic like MTL (Metric Temporal Logic) do not scale with respect to two…

Software Engineering · Computer Science 2015-08-27 Marcello M. Bersani , Domenico Bianculli , Carlo Ghezzi , Srdan Krstic , Pierluigi San Pietro

Fuzzy reasoning is a very productive research field that during the last years has provided a number of theoretical approaches and practical implementation prototypes. Nevertheless, the classical implementations, like Fril, are not adapted…

Programming Languages · Computer Science 2009-03-13 Victor Pablos Ceruelo , Susana Munoz-Hernandez , Hannes Strass

In real-life temporal scenarios, uncertainty and preferences are often essential and coexisting aspects. We present a formalism where quantitative temporal constraints with both preferences and uncertainty can be defined. We show how three…

Artificial Intelligence · Computer Science 2021-04-12 F. Rossi , K. B. Venable , N. Yorke-Smith

The Fuzzy Modeling has been applied in a wide variety of fields such as Engineering and Management Sciences and Social Sciences to solve a number Decision Making Problems which involve impreciseness, uncertainty and vagueness in data. In…

Artificial Intelligence · Computer Science 2013-04-29 Arindam Chaudhuri , Kajal De , Dipak Chatterjee

Fuzziness and randomicity widespread exist in natural science, engineering, technology and social science. The purpose of this paper is to present a new logic - uncertain propositional logic which can deal with both fuzziness by taking…

Logic · Mathematics 2015-06-11 Maokang Luo , Wei He

Humans often communicate by using imprecise language, suggesting that fuzzy concepts with unclear boundaries are prevalent in language use. In this paper, we test the extent to which models trained to capture the distributional statistics…

Computation and Language · Computer Science 2021-04-23 Kanishka Misra , Julia Taylor Rayz

Large Language Models (LLMs) achieve strong performance in analyzing and generating text, yet they struggle with explicit, transparent, and verifiable reasoning over complex texts such as those containing debates. In particular, they lack…

Artificial Intelligence · Computer Science 2026-03-04 Gianvincenzo Alfano , Sergio Greco , Lucio La Cava , Stefano Francesco Monea , Irina Trubitsyna

Previous work has shown that reasoning with real-time temporal logics is often simpler when restricted to models with bounded variability---where no more than v events may occur every V time units, for given v, V. When reasoning about…

Logic in Computer Science · Computer Science 2015-02-24 Carlo A. Furia , Paola Spoletini

Formal properties represent a cornerstone of the system-correctness proofs based on formal verification techniques such as model checking. Formalizing requirements into temporal properties may be very complex and error prone, due not only…

Logic in Computer Science · Computer Science 2017-09-08 Stefano Tonetta

For over a decade, researchers in formal methods tried to create formalisms that permit natural specification of systems and allow mathematical reasoning about their correctness. The availability of fully-automated reasoning tools enables…

Software Engineering · Computer Science 2016-11-17 D. Paun , M. Chechik

Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in…

Artificial Intelligence · Computer Science 2011-06-06 U. Straccia