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Probabilistic Logic Programming (PLP), exemplified by Sato and Kameya's PRISM, Poole's ICL, Raedt et al's ProbLog and Vennekens et al's LPAD, is aimed at combining statistical and logical knowledge representation and inference. A key…

Artificial Intelligence · Computer Science 2012-10-09 Muhammad Asiful Islam , C. R. Ramakrishnan , I. V. Ramakrishnan

In order to prove that the P of problems is different to the NP class, we consider the satisfability problem of propositional calculus formulae, which is an NP-complete problem. It is shown that, for every search algorithm A, there is a set…

Computational Complexity · Computer Science 2007-11-09 Alfredo von Reckow

Computability logic (see http://www.csc.villanova.edu/~japaridz/CL/) is a long-term project for redeveloping logic on the basis of a constructive game semantics, with games seen as abstract models of interactive computational problems.…

Logic in Computer Science · Computer Science 2017-01-11 Giorgi Japaridze

Probabilistic argumentation allows reasoning about argumentation problems in a way that is well-founded by probability theory. However, in practice, this approach can be severely limited by the fact that probabilities are defined by adding…

Artificial Intelligence · Computer Science 2019-03-07 Nico Potyka

The Probabilistic Computational Tree Logic (PCTL) is the main specification formalism for discrete probabilistic systems modeled by Markov chains. Despite serious research attempts, the decidability of PCTL satisfiability and validity…

Logic in Computer Science · Computer Science 2025-05-01 Miroslav Chodil , Antonín Kučera

We introduce the completeness problem for Modal Logic and examine its complexity. For a definition of completeness for formulas, given a formula of a modal logic, the completeness problem asks whether the formula is complete for that logic.…

Logic in Computer Science · Computer Science 2017-09-20 Antonis Achilleos

Probabilistic independence is a useful concept for describing the result of random sampling---a basic operation in all probabilistic languages---and for reasoning about groups of random variables. Nevertheless, existing verification methods…

Programming Languages · Computer Science 2020-07-21 Gilles Barthe , Justin Hsu , Kevin Liao

We study the framework of abductive logic programming extended with integrity constraints. For this framework, we introduce a new measure of the simplicity of an explanation based on its degree of \emph{arbitrariness}: the more arbitrary…

Logic in Computer Science · Computer Science 2020-02-19 Luciano Caroprese , Irina Trubitsyna , Miroslaw Truszczynski , Ester Zumpano

We define a logic of propositional formula schemata adding to the syntax of propositional logic indexed propositions and iterated connectives ranging over intervals parameterized by arithmetic variables. The satisfiability problem is shown…

Logic in Computer Science · Computer Science 2014-01-17 Vincent Aravantinos , Ricardo Caferra , Nicolas Peltier

Modal logics are widely used in computer science. The complexity of modal satisfiability problems has been investigated since the 1970s, usually proving results on a case-by-case basis. We prove a very general classification for a wide…

Computational Complexity · Computer Science 2008-02-14 Edith Hemaspaandra , Henning Schnoor

HyperLTL, the extension of Linear Temporal Logic by trace quantifiers, is a uniform framework for expressing information flow policies by relating multiple traces of a security-critical system. HyperLTL has been successfully applied to…

Logic in Computer Science · Computer Science 2019-12-17 Corto Mascle , Martin Zimmermann

Ibeling et al. (2023). axiomatize increasingly expressive languages of causation and probability, and Mosse et al. (2024) show that reasoning (specifically the satisfiability problem) in each causal language is as difficult, from a…

Logic · Mathematics 2024-05-21 Duligur Ibeling , Thomas F. Icard , Milan Mossé

In probabilistic logic entailments, even moderate size problems can yield linear constraint systems with so many variables that exact methods are impractical. This difficulty can be remedied in many cases of interest by introducing a three…

Artificial Intelligence · Computer Science 2013-03-26 Paul Snow

Generalized Probabilistic Logic (GPL) is a temporal logic, based on the modal mu-calculus, for specifying properties of reactive probabilistic systems. We explore XPL, an extension to GPL allowing the semantics of nondeterminism present in…

Logic in Computer Science · Computer Science 2017-05-10 Andrey Gorlin , C. R. Ramakrishnan

Efforts to apply transformer-based language models (TLMs) to the problem of reasoning in natural language have enjoyed ever-increasing success in recent years. The most fundamental task in this area to which nearly all others can be reduced…

Computation and Language · Computer Science 2025-08-26 Tharindu Madusanka , Ian Pratt-Hartmann , Riza Batista-Navarro

We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability…

Probability · Mathematics 2020-03-17 Giuseppe Sanfilippo , Angelo Gilio , David Over , Niki Pfeifer

Inductive Logic Programming (ILP) provides interpretable rule learning in relational domains, yet remains limited in its ability to induce and reason with numerical constraints. Classical ILP systems operate over discrete predicates and…

Artificial Intelligence · Computer Science 2025-12-16 Nijesh Upreti , Vaishak Belle

Propositional Linear Temporal Logic (LTL) is a popular formalism for specifying desirable requirements and security and privacy policies for software, networks, and systems. Yet expressing such requirements and policies in LTL remains…

Logic in Computer Science · Computer Science 2026-04-09 Priscilla Kyei Danso , Mohammad Saqib Hasan , Niranjan Balasubramanian , Omar Chowdhury

Sandqvist gave a proof-theoretic semantics (P-tS) for classical logic (CL) that explicates the meaning of the connectives without assuming bivalance. Later, he gave a semantics for intuitionistic propositional logic (IPL). While soundness…

Logic · Mathematics 2025-07-18 Alexander V. Gheorghiu

Probabilistic Logic Programming is an effective formalism for encoding problems characterized by uncertainty. Some of these problems may require the optimization of probability values subject to constraints among probability distributions…

Logic in Computer Science · Computer Science 2023-06-22 Damiano Azzolini , Fabrizio Riguzzi