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We study probabilistic complexity classes and questions of derandomisation from a logical point of view. For each logic L we introduce a new logic BPL, bounded error probabilistic L, which is defined from L in a similar way as the…

Logic in Computer Science · Computer Science 2015-07-01 Kord Eickmeyer , Martin Grohe

Classical countably additive real-valued probabilities come at a philosophical cost: in many infinite situations, they assign the same probability value -- namely, zero -- to cases that are impossible as well as to cases that are possible.…

Probability · Mathematics 2022-08-29 Alexander R. Pruss

In the present paper we prove the compactness theorem with respect to partial structures and quasi-truth, using the technique of ultraproducts. Partial structures and quasi-truth are two notions developed within the partial structures…

Logic · Mathematics 2024-05-20 Rodolfo Cunha Carnier

We investigate the end extendibility of models of arithmetic with restricted elementarity. By utilizing the restricted ultrapower construction in the second-order context, for each $n\in\mathbb{N}$ and any countable model of…

Logic · Mathematics 2024-09-12 Mengzhou Sun

Recently maximum pseudo-likelihood (MPL) inference method has been successfully applied to statistical physics models with intractable likelihoods. We use information theory to derive a relation between the pseudo-likelihood and likelihood…

Disordered Systems and Neural Networks · Physics 2015-06-18 Alexander Mozeika , Onur Dikmen , Joonas Piili

Every mathematical structure has an elementary extension to a pseudo-countable structure, one that is seen as countable inside a suitable class model of set theory, even though it may actually be uncountable. This observation, proved easily…

Logic · Mathematics 2022-10-11 Joel David Hamkins

We define and study logics in the framework of probabilistic team semantics and over metafinite structures. Our work is paralleled by the recent development of novel axiomatizable and tractable logics in team semantics that are closed under…

Logic in Computer Science · Computer Science 2021-04-12 Miika Hannula , Minna Hirvonen , Juha Kontinen

We consider finite relational signatures $\tau \subseteq \sigma$, a sequence of finite base $\tau$-structures $(\mathcal{B}_n : n \in \mathbb{N})$ the cardinalities of which tend to infinity and such that, for some number $\Delta$, the…

Logic · Mathematics 2025-11-11 Vera Koponen

Inference for high-dimensional hidden Markov models is challenging due to the exponential-in-dimension computational cost of calculating the likelihood. To address this issue, we introduce an innovative composite likelihood approach called…

Methodology · Statistics 2025-01-17 Lorenzo Rimella , Chris Jewell , Paul Fearnhead

Provability logics are modal or polymodal systems designed for modeling the behavior of G\"odel's provability predicate in arithmetical theories and its natural extensions. If \Lambda is any ordinal, the G\"odel-L\"ob calculus GLP(\Lambda)…

Logic · Mathematics 2013-07-05 David Fernández-Duque

Let $L$ be a countable language. We characterize, in terms of definable closure, those countable theories $\Sigma$ of $\mathcal{L}_{\omega_1, \omega}(L)$ for which there exists an $S_\infty$-invariant probability measure on the collection…

Logic · Mathematics 2017-10-18 Nathanael Ackerman , Cameron Freer , Rehana Patel

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility…

Artificial Intelligence · Computer Science 2016-08-31 Nir Friedman , Joseph Y. Halpern

We present SGDPLL(T), an algorithm that solves (among many other problems) probabilistic inference modulo theories, that is, inference problems over probabilistic models defined via a logic theory provided as a parameter (currently,…

Artificial Intelligence · Computer Science 2016-05-30 Rodrigo de Salvo Braz , Ciaran O'Reilly , Vibhav Gogate , Rina Dechter

In spite of the rapidly increasing number of applications of machine learning in various domains, a principled and systematic approach to the incorporation of domain knowledge in the engineering process is still lacking and ad hoc solutions…

Artificial Intelligence · Computer Science 2019-07-29 Mark-Oliver Stehr , Minyoung Kim , Carolyn L. Talcott , Merrill Knapp , Akos Vertes

We present a probabilistic extension of the description logic $\mathcal{ALC}$ for reasoning about statistical knowledge. We consider conditional statements over proportions of the domain and are interested in the probabilistic-logical…

Artificial Intelligence · Computer Science 2017-06-13 Rafael Peñaloza , Nico Potyka

Complexity classes such as $\#\mathbf{P}$, $\oplus\mathbf{P}$, $\mathbf{GapP}$, $\mathbf{OptP}$, $\mathbf{NPMV}$, or the class of fuzzy languages realised by polynomial-time fuzzy nondeterministic Turing machines, can all be described in…

Formal Languages and Automata Theory · Computer Science 2024-08-20 Peter Kostolányi

There are two main approach to probability, one of set-theoretic character where probability is the measure of a set, and another one of linguistic character where probability is the degree of confidence in a proposition. In this work we…

Logic · Mathematics 2013-10-24 Maurizio Negri

We investigate cut-elimination and cut-simulation in impredicative (higher-order) logics. We illustrate that adding simple axioms such as Leibniz equations to a calculus for an impredicative logic -- in our case a sequent calculus for…

Logic in Computer Science · Computer Science 2019-03-14 Christoph Benzmueller , Chad E. Brown , Michael Kohlhase

We study the finite model property of subframe logics with expressible transitive reflexive closure modality. For $m>0$, let $\mathrm{L}_m$ be the logic defined by axiom $\lozenge^{m+1} p\to \lozenge p\vee p$. We construct filtrations for…

Logic · Mathematics 2025-06-16 Andrey Kudinov , Ilya Shapirovsky

In [12], Nilsson proposed the probabilistic logic in which the truth values of logical propositions are probability values between 0 and 1. It is applicable to any logical system for which the consistency of a finite set of propositions can…

Artificial Intelligence · Computer Science 2013-04-12 Su-shing Chen