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Formal logic enables computers to reason in natural language by representing sentences in symbolic forms and applying rules to derive conclusions. However, in what our study characterizes as "rulebreaker" scenarios, this method can lead to…

Computation and Language · Computer Science 2025-08-18 Jason Chan , Robert Gaizauskas , Zhixue Zhao

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modelling tools to…

Artificial Intelligence · Computer Science 2023-04-18 Pietro Totis , Angelika Kimmig , Luc De Raedt

There is a wide range of modal logics whose semantics goes beyond relational structures, and instead involves, e.g., probabilities, multi-player games, weights, or neighbourhood structures. Coalgebraic logic serves as a unifying semantic…

Logic in Computer Science · Computer Science 2023-06-16 Oliver Görlitz , Daniel Hausmann , Merlin Humml , Dirk Pattinson , Simon Prucker , Lutz Schröder

Sequential propositional logic deviates from ordinary propositional logic by taking into account that during the sequential evaluation of a propositional statement,atomic propositions may yield different Boolean values at repeated…

Logic in Computer Science · Computer Science 2011-06-28 J. A. Bergstra , A. Ponse

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

We present a novel unity of logic, viz., a single sequent calculus that embodies classical, intuitionistic and linear logics. Concretely, we define classical linear logic negative (CLL$^-$), a new logic that is classical and linear yet…

Logic · Mathematics 2021-01-08 Norihiro Yamada

Differentiable Logics are deployed in neuro-symbolic learning tasks as a way of embedding logical constraints in the training objective of neural networks. A differentiable logic consists of a syntax to write logical properties and a…

Logic in Computer Science · Computer Science 2026-05-19 Thomas Flinkow , Ekaterina Komendantskaya , Matteo Capucci , Rosemary Monahan

Logic programming with tabling and constraints (TCLP, tabled constraint logic programming) has been shown to be more expressive and, in some cases, more efficient than LP, CLP, or LP with tabling. In this paper we provide insights regarding…

Logic in Computer Science · Computer Science 2020-10-01 Joaquín Arias , Manuel Carro

In this survey, we present in a unified way the categorical and syntactical settings of coherent differentiation introduced recently, which shows that the basic ideas of differential linear logic and of the differential lambda-calculus are…

Logic in Computer Science · Computer Science 2024-01-29 Thomas Ehrhard

Current evaluations of Continual Learning (CL) methods typically assume that there is no constraint on training time and computation. This is an unrealistic assumption for any real-world setting, which motivates us to propose: a practical…

Ordered logics and type systems have been used in a variety of applications including computational linguistics, memory allocation, stream processing, logical frameworks, parametricity, and enforcing security protocols. In most…

Logic in Computer Science · Computer Science 2026-05-20 Sophia Roshal , Frank Pfenning

Defeasible statements are statements that are likely, or probable, or usually true, but may occasionally be false. Plausible reasoning makes conclusions from statements that are either facts or defeasible statements without using numbers.…

Artificial Intelligence · Computer Science 2026-04-22 David Billington

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 2019-09-19 Daniel Neider , Alexander Weinert , Martin Zimmermann

It is well known that we can use structural proof theory to refine, or generalize, existing paradigmatic computational primitives, or to discover new ones. Under such a point of view we keep developing a programme whose goal is establishing…

Logic in Computer Science · Computer Science 2012-12-20 Luca Roversi

Propositional Dynamic Logic, PDL, is a modal logic designed to formalize the reasoning about programs. By extending accessibility between states to states and state sets, concurrent propositional dynamic logic CPDL, is introduced to include…

Logic in Computer Science · Computer Science 2025-01-17 Chun-Yu Lin

This article presents an overview of computability logic -- the game-semantically constructed logic of interactive computational tasks and resources. There is only one non-overview, technical section in it, devoted to a proof of the…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

{\em Computability logic} (CoL) is a powerful, mathematically rigorous computational model. In this paper, we show that CoL-web, a web extension to CoL, naturally supports web programming where database updates are involved. To be specific,…

Artificial Intelligence · Computer Science 2021-01-25 Keehang Kwon

The main contribution of this paper is the introduction of a dynamic logic formalism for reasoning about information flow in composite quantum systems. This builds on our previous work on a complete quantum dynamic logic for single systems.…

Quantum Physics · Physics 2021-10-05 Alexandru Baltag , Sonja Smets

This article looks at how reasoning works in current Large Language Models (LLMs) that function using the token-completion method. It examines their stochastic nature and their similarity to human abductive reasoning. The argument is that…

Computation and Language · Computer Science 2025-12-12 Luciano Floridi , Jessica Morley , Claudio Novelli , David Watson

We introduce kLog, a novel approach to statistical relational learning. Unlike standard approaches, kLog does not represent a probability distribution directly. It is rather a language to perform kernel-based learning on expressive logical…

Artificial Intelligence · Computer Science 2014-10-17 Paolo Frasconi , Fabrizio Costa , Luc De Raedt , Kurt De Grave