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Part of the theory of logic programming and nonmonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more…

Artificial Intelligence · Computer Science 2007-05-23 Pascal Hitzler , Matthias Wendt

The semantic web is an open and distributed environment in which it is hard to guarantee consistency of knowledge and information. Under the standard two-valued semantics everything is entailed if knowledge and information is inconsistent.…

Artificial Intelligence · Computer Science 2014-05-01 Wenzhao Qiao , Nico Roos

We study the faithfulness of an explanation system to the underlying prediction model. We show that this can be captured by two properties, consistency and sufficiency, and introduce quantitative measures of the extent to which these hold.…

Machine Learning · Computer Science 2022-02-03 Sanjoy Dasgupta , Nave Frost , Michal Moshkovitz

In this paper, we focus on discrete-time stochastic systems modelled by nonlinear stochastic difference equations and propose robust abstractions for verifying probabilistic linear temporal specifications. The current literature focuses on…

Probability · Mathematics 2022-05-05 Yiming Meng , Jun Liu

We define a novel, extensional, three-valued semantics for higher-order logic programs with negation. The new semantics is based on interpreting the types of the source language as three-valued Fitting-monotonic functions at all levels of…

Programming Languages · Computer Science 2019-07-25 Angelos Charalambidis , Panos Rondogiannis , Ioanna Symeonidou

The intuitive notion of evidence has both semantic and syntactic features. In this paper, we develop an {\em evidence logic} for epistemic agents faced with possibly contradictory evidence from different sources. The logic is based on a…

Logic · Mathematics 2013-07-05 Johan van Benthem , David Fernández-Duque , Eric Pacuit

Conditional independence is a crucial concept supporting adequate modelling and efficient reasoning in probabilistics. In knowledge representation, the idea of conditional independence has also been introduced for specific formalisms, such…

Artificial Intelligence · Computer Science 2024-12-19 Jesse Heyninck

Proof search has been used to specify a wide range of computation systems. In order to build a framework for reasoning about such specifications, we make use of a sequent calculus involving induction and co-induction. These proof principles…

Logic in Computer Science · Computer Science 2009-09-30 Alwen Tiu , Alberto Momigliano

Logic has proved essential for formally modeling software based systems. Such formal descriptions, frequently called specifications, have served not only as requirements documentation and formalisation, but also for providing the…

Logic in Computer Science · Computer Science 2021-07-20 Carlos G. Lopez Pombo , Thomas S. E. Maibaum

In recent years, there has been an increased need for the use of active systems - systems required to act automatically based on events, or changes in the environment. Such systems span many areas, from active databases to applications that…

Artificial Intelligence · Computer Science 2012-07-09 Segev Wasserkrug , Avigdor Gal , Opher Etzion

In this report, we present a formal model of fair iteration of events for B event systems. The model is used to justify proof obligations for basic liveness properties and preservation under refinement of general liveness properties. The…

Logic in Computer Science · Computer Science 2007-05-23 Hector Ruiz Barradas , Didier Bert

The formal analysis of automated systems is an important and growing industry. This activity routinely requires new verification frameworks to be developed to tackle new programming features, or new considerations (bugs of interest). Often,…

Logic in Computer Science · Computer Science 2026-02-17 Paul Brunet

In logic programming, negation can be interpreted in various ways. Probably best known is the concept of "negation as failure", where "$\mathit{not}\, p$" is true if we have no evidence for $p$. On the other hand, strong negation requires…

Logic in Computer Science · Computer Science 2026-05-25 Pascal Kettmann , Hannes Strass , Jesse Heyninck , Jeroen Spaans

This paper proposes SCALES, a general framework that translates well-established fairness principles into a common representation based on the Constraint Markov Decision Process (CMDP). With the help of causal language, our framework can…

Machine Learning · Computer Science 2022-09-23 Sreejith Balakrishnan , Jianxin Bi , Harold Soh

Argumentation is a very active research field of Artificial Intelligence concerned with the representation and evaluation of arguments used in dialogues between humans and/or artificial agents. Acceptability semantics of formal…

Artificial Intelligence · Computer Science 2025-03-05 Zlatina Mileva , Antonis Bikakis , Fabio Aurelio D'Asaro , Mark Law , Alessandra Russo

We give a presentation of Pure type systems where contexts need not be well-formed and show that this presentation is equivalent to the usual one. The main motivation for this presentation is that, when we extend Pure type systems with…

Logic in Computer Science · Computer Science 2021-07-19 Gilles Dowek

We construct witnesses that can be used to derive strategies in fixpoint games and provide proof that the least fixpoint of a function is either above or not below some given bound. We rely on a lattice-theoretical approach, including a…

Logic in Computer Science · Computer Science 2026-03-13 Barbara König , Karla Messing

Event argument extraction identifies arguments for predefined event roles in text. Existing work evaluates this task with exact match (EM), where predicted arguments must align exactly with annotated spans. While suitable for span-based…

Computation and Language · Computer Science 2025-09-11 Omar Sharif , Joseph Gatto , Madhusudan Basak , Sarah M. Preum

As learning machines increase their influence on decisions concerning human lives, analyzing their fairness properties becomes a subject of central importance. Yet, our best tools for measuring the fairness of learning systems are rigid…

Machine Learning · Statistics 2022-07-21 David Lopez-Paz , Diane Bouchacourt , Levent Sagun , Nicolas Usunier

In this paper we explore a unifying approach --- that of hypotheses assumption --- as a means to provide a semantics for all Normal Logic Programs (NLPs), the Minimal Hypotheses (MH) semantics. This semantics takes a positive hypotheses…

Logic in Computer Science · Computer Science 2011-08-31 Alexandre Miguel Pinto , Luś Moniz Pereira
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