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We design a proof system for propositional classical logic that integrates two languages for Boolean functions: standard conjunction-disjunction-negation and binary decision trees. We give two reasons to do so. The first is…

Logic in Computer Science · Computer Science 2022-07-01 Chris Barrett , Alessio Guglielmi

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

Models of complex systems are widely used in the physical and social sciences, and the concept of layering, typically building upon graph-theoretic structure, is a common feature. We describe an intuitionistic substructural logic called…

Logic in Computer Science · Computer Science 2023-06-22 Simon Docherty , David Pym

Intuitionistic grammar logics fuse constructive and multi-modal reasoning while permitting the use of converse modalities, serving as a generalization of standard intuitionistic modal logics. In this paper, we provide definitions of these…

Logic in Computer Science · Computer Science 2025-12-04 Tim S. Lyon

In many instances in first order logic or computable algebra, classical theorems show that many problems are undecidable for general structures, but become decidable if some rigidity is imposed on the structure. For example, the set of…

Discrete Mathematics · Computer Science 2017-08-08 Emmanuel Jeandel

Tarski gave a general semantics for deductive reasoning: a formula a may be deduced from a set A of formulas iff a holds in all models in which each of the elements of A holds. A more liberal semantics has been considered: a formula a may…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

Many tasks in statistical and causal inference can be construed as problems of \emph{entailment} in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for \emph{causal}…

Logic in Computer Science · Computer Science 2023-06-02 Milan Mossé , Duligur Ibeling , Thomas Icard

First-order temporal logics are notorious for their bad computational behaviour. It is known that even the two-variable monadic fragment is highly undecidable over various linear timelines, and over branching time even one-variable…

Logic in Computer Science · Computer Science 2015-08-17 Christopher Hampson , Agi Kurucz

Bernays introduced a method for proving underivability results in propositional calculi by truth tables. In general, this motivates an investigations of how to find, given a propositional logic, a finite-valued logic which has as few…

Logic · Mathematics 2022-01-31 Matthias Baaz , Richard Zach

Argumentation is a non-monotonic process. This reflects the fact that argumentation involves uncertain information, and so new information can cause a change in the conclusions drawn. However, the base logic does not need to be…

Artificial Intelligence · Computer Science 2018-09-05 Anthony Hunter

Linear-time computational techniques have been developed for combining evidence which is available on a number of contending hypotheses. They offer a means of making the computation-intensive calculations involved more efficient in certain…

Artificial Intelligence · Computer Science 2012-07-02 Yaxin Bi , Jiwen W. Guan

After surveying classical results, we introduce a generalized notion of inference system to support structural recursion on non-well-founded data types. Besides axioms and inference rules with the usual meaning, a generalized inference…

Logic in Computer Science · Computer Science 2018-04-23 Francesco Dagnino

An increasing number of scientific experiments support the view of perception as Bayesian inference, which is rooted in Helmholtz's view of perception as unconscious inference. Recent study of logic presents a view of logical reasoning as…

Artificial Intelligence · Computer Science 2026-02-24 Hiroyuki Kido

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

We provide a logical framework in which a resource-bounded agent can be seen to perform approximations of probabilistic reasoning. Our main results read as follows. First we identify the conditions under which propositional probability…

Logic in Computer Science · Computer Science 2022-05-09 Paolo Baldi , Hykel Hosni

Probabilistic programming is considered as a framework, in which basic components of cognitive architectures can be represented in unified and elegant fashion. At the same time, necessity of adopting some component of cognitive…

Artificial Intelligence · Computer Science 2016-05-05 Alexey Potapov

Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated…

Artificial Intelligence · Computer Science 2024-07-09 Andrei Popescu , Johannes P. Wallner

Spatial conjunction is a powerful construct for reasoning about dynamically allocated data structures, as well as concurrent, distributed and mobile computation. While researchers have identified many uses of spatial conjunction, its…

Logic in Computer Science · Computer Science 2007-05-23 Viktor Kuncak , Martin Rinard

In a previously published ENTCS paper (Santos et al. (2016)), we introduced a sequent calculus called $\mathbf{LMT^{\rightarrow}}$ for Minimal Implicational Propositional Logic ($\mathbf{LMT^{\rightarrow}}$). This calculus provides a proof…

Logic in Computer Science · Computer Science 2020-02-04 Jefferson de Barros Santos , Bruno Lopes Vieira , Edward Hermann Haeusler

While probability theory is normally applied to external environments, there has been some recent interest in probabilistic modeling of the outputs of computations that are too expensive to run. Since mathematical logic is a powerful tool…

Artificial Intelligence · Computer Science 2016-10-10 Scott Garrabrant , Benya Fallenstein , Abram Demski , Nate Soares