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Large Language Models (LLMs) are expected to be predictable and trustworthy to support reliable decision-making systems. Yet current LLMs often show inconsistencies in their judgments. In this work, we examine logical preference consistency…

Computation and Language · Computer Science 2025-02-11 Yinhong Liu , Zhijiang Guo , Tianya Liang , Ehsan Shareghi , Ivan Vulić , Nigel Collier

The paper considers algorithmic properties of classical and non-classical first-order logics and theories in bounded languages. The main idea is to prove the undecidability of various fragments of classical and non-classical first-order…

Logic · Mathematics 2025-05-02 Mikhail Rybakov

We extend the inflationary fixed-point logic, IFP, with a new kind of second-order quantifiers which have (poly-)logarithmic bounds. We prove that on ordered structures the new logic $\exists^{\log^{\omega}}\text{IFP}$ captures the limited…

Logic in Computer Science · Computer Science 2022-09-07 Kexu Wang , Xishun Zhao

Digraphs provide an alternative syntax for propositional logic, with digraph kernels corresponding to classical models. Semikernels generalize kernels and we identify a subset of well-behaved semikernels that provides nontrivial models for…

Logic · Mathematics 2019-06-11 Michal Walicki , Sjur Dyrkolbotn

This paper presents a logic of preference and functional dependence (LPFD) and its hybrid extension (HLPFD), both of whose sound and strongly complete axiomatization are provided. The decidability of LPFD is also proved. The application of…

Computer Science and Game Theory · Computer Science 2022-09-20 Qian Chen , Chenwei Shi , Yiyan Wang

The aim of this article is to generalize logics of formal inconsistency ($\textbf{LFI}$s) to systems dealing with the concept of incompatibility, expressed by means of a binary connective. The basic idea is that having two incompatible…

Logic · Mathematics 2022-02-23 Marcelo Esteban Coniglio , Guilherme Vicentin de Toledo

Large language models exhibit systematic limitations in structured logical reasoning: they conflate hypothesis generation with verification, cannot distinguish conjecture from validated knowledge, and allow weak reasoning steps to propagate…

Artificial Intelligence · Computer Science 2026-04-20 Sankalp Gilda , Shlok Gilda

During the last decades, a lot of effort was put into identifying decidable fragments of first-order logic. Such efforts gave birth, among the others, to the two-variable fragment and the guarded fragment, depending on the type of…

Logic in Computer Science · Computer Science 2021-10-05 Bartosz Bednarczyk , Maja Orłowska , Anna Pacanowska , Tony Tan

We present some hypersequent calculi for all systems of the classical cube and their extensions with axioms $T$, $P$, $D$, and, for every $n\geq 1$, rule $RD^+_n$. The calculi are internal as they only employ the language of the logic, plus…

Logic in Computer Science · Computer Science 2020-06-11 Tiziano Dalmonte , Björn Lellmann , Nicola Olivetti , Elaine Pimentel

Following the lines of the analysis done in [BPZ07, BCF07] for first-order G\"odel logics, we present an analogous investigation for Nilpotent Minimum logic NM. We study decidability and reciprocal inclusion of various sets of first-order…

Logic · Mathematics 2012-07-03 Matteo Bianchi

Logic Programs with Ordered Disjunction (LPODs) extend classical logic programs with the capability of expressing alternatives with decreasing degrees of preference in the heads of program rules. Despite the fact that the operational…

Artificial Intelligence · Computer Science 2022-05-09 Angelos Charalambidis , Panos Rondogiannis , Antonis Troumpoukis

Monadic second order logic is the expansion of first order logic by quantifiers ranging over unary relations. We study the shared monadic second order theory of finite linear orders, i.e. the pseudofinite monadic second order theory of…

Logic · Mathematics 2021-05-27 Deacon Linkhorn

There is knowledge. There is belief. And there is tacit agreement.' 'We may talk about objects. We may talk about attributes of the objects. Or we may talk both about objects and their attributes.' This work inspects tacit agreements on…

Artificial Intelligence · Computer Science 2014-04-25 Ryuta Arisaka

We provide a denotational semantics for first-order logic that captures the two-level view of the computation process typical for constraint programming. At one level we have the usual program execution. At the other level an automatic…

Logic in Computer Science · Computer Science 2007-05-23 K. R. Apt , C. F. M. Vermeulen

Coherence with respect to Kelly-Mac Lane graphs is proved for categories that correspond to the multiplicative fragment without constant propositions of classical linear first-order predicate logic without or with mix. To obtain this…

Logic · Mathematics 2014-06-18 K. Dosen , Z. Petric

Logical frameworks provide natural and direct ways of specifying and reasoning within deductive systems. The logical framework LF and subsequent developments focus on finitary proof systems, making the formalization of circular proof…

Logic in Computer Science · Computer Science 2023-05-11 Zhibo Chen , Frank Pfenning

We provided in \cite{BaldwinBrincusI} extensions of first order logic by modified inferential definitions of the classical $\omega$-rule in $1$ or $2$ sorts. These logics are categorical in the inferential sense. Arithmetic has a unique…

Logic · Mathematics 2026-04-29 John T. Baldwin , Constantin C. Brîncuş

Classical higher-order logic, when utilized as a meta-logic in which various other (classical and non-classical) logics can be shallowly embedded, is well suited for realising a universal logic reasoning approach. Universal logic reasoning…

Artificial Intelligence · Computer Science 2017-03-29 Christoph Benzmüller

We consider the problem of answering queries about formulas of first-order logic based on background knowledge partially represented explicitly as other formulas, and partially represented as examples independently drawn from a fixed…

Artificial Intelligence · Computer Science 2019-06-25 Vaishak Belle , Brendan Juba

Lifting attempts to speed up probabilistic inference by exploiting symmetries in the model. Exact lifted inference methods, like their propositional counterparts, work by recursively decomposing the model and the problem. In the…

Artificial Intelligence · Computer Science 2013-06-05 Nima Taghipour , Jesse Davis , Hendrik Blockeel
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