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Related papers: Size and Logic

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We recall the notion of abstract bornology, and connect it with topological spaces and size functions. As a generalization of measures of non-compactness, we show how every size function can be mapped to a maxitive measure.

General Mathematics · Mathematics 2022-06-06 Paul Poncet

While neural models show remarkable accuracy on individual predictions, their internal beliefs can be inconsistent across examples. In this paper, we formalize such inconsistency as a generalization of prediction error. We propose a…

Artificial Intelligence · Computer Science 2019-09-16 Tao Li , Vivek Gupta , Maitrey Mehta , Vivek Srikumar

We present a simple new method for proving that languages are not regular. We prove the correctness of the method, illustrate the ease of using the method on well-known examples of nonregular languages, and prove two additional theorems on…

Formal Languages and Automata Theory · Computer Science 2020-01-27 Jack H. Lutz , Giora Slutzki

Real-valued logics underlie an increasing number of neuro-symbolic approaches, though typically their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of…

Logic in Computer Science · Computer Science 2022-09-01 Ronald Fagin , Ryan Riegel , Alexander Gray

Logics with team semantics provide alternative means for logical characterization of complexity classes. Both dependence and independence logic are known to capture non-deterministic polynomial time, and the frontiers of tractability in…

Logic in Computer Science · Computer Science 2019-03-27 Miika Hannula , Lauri Hella

(l) I have enough evidence to render the sentence S probable. (la) So, relative to what I know, it is rational of me to believe S. (2) Now that I have more evidence, S may no longer be probable. (2a) So now, relative to what I know, it is…

Artificial Intelligence · Computer Science 2016-11-26 Henry E. Kyburg

We explore a definition of complexity based on logic functions, which are widely used as compact descriptions of rules in diverse fields of contemporary science. Detailed numerical analysis shows that (i) logic complexity is effective in…

Data Analysis, Statistics and Probability · Physics 2016-03-11 Marco Gherardi , Pietro Rotondo

Beginning with a simple semantics for propositions, based on counting observations, it is shown that probabilistic and fuzzy logic correspond to two different heuristic assumptions regarding the combination of propositions whose evidence…

Artificial Intelligence · Computer Science 2020-09-29 Ben Goertzel

Linear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources, and non monotonic reasoning in particular to represent exceptions. Recently, a framework to combine…

Artificial Intelligence · Computer Science 2019-08-19 Francesco Olivieri , Guido Governatori , Claudio Tomazzoli , Matteo Cristani

This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for principled reasons not addressable with probabilistic means);…

Artificial Intelligence · Computer Science 2017-03-02 Tarek R. Besold , Artur d'Avila Garcez , Keith Stenning , Leendert van der Torre , Michiel van Lambalgen

We introduce and study logic programs whose clauses are built out of monotone constraint atoms. We show that the operational concept of the one-step provability operator generalizes to programs with monotone constraint atoms, but the…

Artificial Intelligence · Computer Science 2007-05-23 V. W. Marek , I. Niemela , M. Truszczynski]

Time evolution of the cities and of the languages is considered in terms of multiplicative noise and fragmentation processes; where power law (Pareto-Zipf law) and slightly asymmetric log-normal (Gauss) distribution result for the size…

Physics and Society · Physics 2009-11-13 C. Tuncay

We present a method of generating first-order logic statements whose complexity can be controlled along multiple dimensions. We use this method to automatically create several datasets consisting of questions asking for the truth or falsity…

Machine Learning · Computer Science 2025-02-21 Shokhrukh Ibragimov , Arnulf Jentzen , Benno Kuckuck

Graded modal logics generalise standard modal logics via families of modalities indexed by an algebraic structure whose operations mediate between the different modalities. The graded "of-course" modality $!_r$ captures how many times a…

Logic in Computer Science · Computer Science 2024-11-26 Victoria Vollmer , Danielle Marshall , Harley Eades , Dominic Orchard

Given a sequence of integers $a_j, j\ge 1,$ a multiset is a combinatorial object composed of unordered components, such that there are exactly $a_j$ one-component multisets of size $j.$ When $a_j\asymp j^{r-1} y^j$ for some $r>0$, $y\geq…

Combinatorics · Mathematics 2007-06-13 Boris L. Granovsky , Dudley Stark

This is a paper about geometry and how one can derive several fundamental laws of physics from a simple postulate of geometrical nature. The method uses monogenic functions analysed in the algebra of 5-dimensional spacetime, exploring the…

General Physics · Physics 2007-05-23 Jose B. Almeida

We construct a polygonal spiral by arranging a sequence of regular $n$-gons such that each $n$-gon shares a specified side and vertex with the $(n+1)$-gon in the construction. By offering flexibility for determining the size of each $n$-gon…

Metric Geometry · Mathematics 2024-04-16 Kyle Fridberg

We discuss two main ways in comparing and evaluating the size of sets: the "Cantorian" way, grounded on the so called Hume principle (two sets have equal size if they are equipotent), and the "Euclidean" way, maintaining Euclid's principle…

Logic · Mathematics 2022-12-13 Marco Forti

We introduce a logic for reasoning about evidence, that essentially views evidence as a function from prior beliefs (before making an observation) to posterior beliefs (after making the observation). We provide a sound and complete…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

In this paper, we study the ability of large language models to learn specific mathematical rules such as distributivity or simplifying equations. We present an empirical analysis of their ability to generalize these rules, as well as to…

Computation and Language · Computer Science 2024-10-28 Antoine Gorceix , Bastien Le Chenadec , Ahmad Rammal , Nelson Vadori , Manuela Veloso