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In abstract argumentation, multiple argumentation semantics have been proposed that allow to select sets of jointly acceptable arguments from a given argumentation framework, i.e. based only on the attack relation between arguments. The…

Artificial Intelligence · Computer Science 2019-02-28 Marcos Cramer , Mathieu Guillaume

Ambiguity is a natural language phenomenon occurring at different levels of syntax, semantics, and pragmatics. It is widely studied; in Psycholinguistics, for instance, we have a variety of competing studies for the human disambiguation…

Computation and Language · Computer Science 2023-11-16 Daphne Wang , Mehrnoosh Sadrzadeh

Large Language Models (LLMs) exhibit impressive reasoning abilities, yet their reliance on structured step-by-step processing reveals a critical limitation. In contrast, human cognition fluidly adapts between intuitive, heuristic (System 1)…

Computation and Language · Computer Science 2025-10-16 Alireza S. Ziabari , Nona Ghazizadeh , Zhivar Sourati , Farzan Karimi-Malekabadi , Payam Piray , Morteza Dehghani

Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those…

Artificial Intelligence · Computer Science 2014-08-08 Joseph Y. Halpern

In fuzzy theory of sets and groups, the use of $\alpha$--levels is a standard to translate problems from the fuzzy to the crisp framework. Using strong $\alpha$--levels, it is possible to establish a one to one correspondence which makes…

Logic · Mathematics 2021-02-08 Josefa M. Garcia , Pascual Jara

An interval-valued fuzzy answer set programming paradigm is proposed for nonmonotonic reasoning with vague and uncertain information. The set of sub-intervals of $[0,1]$ is considered as truth-space. The intervals are ordered using…

Artificial Intelligence · Computer Science 2020-08-06 Sandip Paul , Kumar Sankar Ray , Diganta Saha

In this paper, we discuss different models for human logic systems and describe a game with nature. G\"odel`s incompleteness theorem is taken into account to construct a model of logical networks based on axioms obtained by symmetry…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Fariel Shafee

In this paper we present, by way of case studies, a proof of concept, based on a prototype working on a automotive data set, aimed at showing the potential usefulness of using formulas of {\L}ukasiewicz propositional logic to query…

Logic in Computer Science · Computer Science 2015-12-04 Stefano Aguzzoli , Pietro Codara , Tommaso Flaminio , Brunella Gerla , Diego Valota

While Large Language Models (LLMs) are widely documented to be sensitive to minor prompt perturbations and prone to sycophantic alignment, their robustness in consequential, rule-bound decision-making remains under-explored. We uncover a…

Artificial Intelligence · Computer Science 2026-04-07 Jon Chun , Katherine Elkins

The theory of fuzzy sets has a wide range of applications, one of which is that of fuzzy groups . The fuzzy sets were introduced by Zadeh. Even though, the story of fuzzy logic started much earlier, it was specially designed mathematically…

General Mathematics · Mathematics 2022-12-20 Sunday Adesina Adebisi , Mike. Ogiugo , Michael Enioluwafe

Dialectical frameworks are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. Their generality allow them to cover a number of…

Artificial Intelligence · Computer Science 2024-07-03 Jesse Heyninck , Matthias Knorr , João Leite

Large Language Models (LLMs) offer natural language explanations as an alternative to feature attribution methods for model interpretability. However, despite their plausibility, they may not reflect the model's true reasoning faithfully.…

Computation and Language · Computer Science 2025-12-29 Kerem Zaman , Shashank Srivastava

Large language models (LLMs) have shown remarkable reasoning capabilities given chain-of-thought prompts (examples with intermediate reasoning steps). Existing benchmarks measure reasoning ability indirectly, by evaluating accuracy on…

Computation and Language · Computer Science 2023-03-03 Abulhair Saparov , He He

Possibilistic logic, an extension of first-order logic, deals with uncertainty that can be estimated in terms of possibility and necessity measures. Syntactically, this means that a first-order formula is equipped with a possibility degree…

Artificial Intelligence · Computer Science 2013-02-28 Bernhard Hollunder

Pythagorean fuzzy sets provide stronger ability than intuitionistic fuzzy sets to model uncertainty information and knowledge, but little effort has been paid to conflict analysis of Pythagorean fuzzy information systems. In this paper, we…

Artificial Intelligence · Computer Science 2017-07-13 Guangming Lang

In this paper we prove soundness and completeness of some epistemic extensions of G\"odel fuzzy logic, based on Kripke models in which both propositions at each state and accessibility relations take values in [0,1]. We adopt belief as our…

Logic · Mathematics 2024-03-05 D. Dastgheib , H. Farahani , A. H. Sharafi

Elaborating a series of intermediate reasoning steps significantly improves the ability of large language models (LLMs) to solve complex problems, as such steps would evoke LLMs to think sequentially. However, human sarcasm understanding is…

Computation and Language · Computer Science 2024-08-27 Ben Yao , Yazhou Zhang , Qiuchi Li , Jing Qin

As one of the longest-running computer-assisted formal mathematics projects, large tracts of mathematical knowledge have been formalized with the help of the Mizar system. Because Mizar is based on first-order classical logic and set…

Logic · Mathematics 2013-11-11 Jesse Alama

This paper undertakes a re-examination of Sir William Hamilton's doctrine of the quantification of the predicate. Hamilton's doctrine comprises two theses. First, the predicates of traditional syllogistic sentence-forms contain implicit…

Logic in Computer Science · Computer Science 2024-04-24 Ian Pratt-Hartmann

Fuzzy description logics serve the representation of vague knowledge, typically letting concepts take truth degrees in the unit interval. Expressiveness, logical properties, and complexity vary strongly with the choice of propositional…

Logic in Computer Science · Computer Science 2025-10-14 Stefan Gebhart , Lutz Schröder , Paul Wild
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