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In this paper I discuss both syntax and semantics of subjective probability. The semantics determines ways of testing probability statements. Among important varieties of subjective probabilities are intersubjective probabilities and…

Artificial Intelligence · Computer Science 2023-09-06 Vladimir Vovk

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

The celebrated Kleene fixed point theorem is crucial in the mathematical modelling of recursive specifications in Denotational Semantics. In this paper we discuss whether the hypothesis of the aforementioned result can be weakened. An…

Information Theory · Computer Science 2024-01-25 Asier Estevan , Juan-José Minãna , Oscar Valero

The different semantics that can be assigned to a logic program correspond to different assumptions made concerning the atoms whose logical values cannot be inferred from the rules. Thus, the well founded semantics corresponds to the…

Logic in Computer Science · Computer Science 2007-05-23 Y. Loyer , N. Spyratos , D. Stamate

Bayesian inference systems should be able to explain their reasoning to users, translating from numerical to natural language. Previous empirical work has investigated the correspondence between absolute probabilities and linguistic…

Artificial Intelligence · Computer Science 2013-04-08 Christopher Elsaesser , Max Henrion

This paper gives a generative model of the interpretation of formal logic for data-driven logical reasoning. The key idea is to represent the interpretation as likelihood of a formula being true given a model of formal logic. Using the…

Artificial Intelligence · Computer Science 2022-03-01 Hiroyuki Kido

We present a propositional logic with fundamental probabilistic semantics, in which each formula is given a real measure in the interval $[0,1]$ that represents its degree of truth. This semantics replaces the binarity of classical logic,…

Logic in Computer Science · Computer Science 2025-05-22 Francisco Aragão

This paper discusses the semantics and proof theory of Nilsson's probabilistic logic, outlining both the benefits of its well-defined model theory and the drawbacks of its proof theory. Within Nilsson's semantic framework, we derive a set…

Artificial Intelligence · Computer Science 2013-04-11 Peter Haddawy , Alan M. Frisch

A natural way to represent beliefs and the process of updating beliefs is presented by Bayesian probability theory, where belief of an agent a in P can be interpreted as a considering that P is more probable than not P. This paper attempts…

Logic in Computer Science · Computer Science 2017-07-28 Jan van Eijck , Kai Li

We develop a domain-theoretic framework for imprecise probability reasoning and inference on general topological spaces with a countably based continuous lattice of open sets. We address two distinct forms of uncertainty: partial or…

Logic in Computer Science · Computer Science 2026-04-13 Abbas Edalat , Pietro Di Gianantonio , Amin Farjudian

Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. Several classical probabilistic inference tasks (such as MAP and computing marginals) have not yet received a lot of attention for…

Artificial Intelligence · Computer Science 2012-02-20 Daan Fierens , Guy Van den Broeck , Ingo Thon , Bernd Gutmann , Luc De Raedt

We introduce a novel logical notion--partial entailment--to propositional logic. In contrast with classical entailment, that a formula P partially entails another formula Q with respect to a background formula set \Gamma intuitively means…

Logic in Computer Science · Computer Science 2014-01-17 Yi Zhou , Yan Zhang

Functional Distributional Semantics provides a computationally tractable framework for learning truth-conditional semantics from a corpus. Previous work in this framework has provided a probabilistic version of first-order logic, recasting…

Computation and Language · Computer Science 2020-06-05 Guy Emerson

Logical entropy gives a measure, in the sense of measure theory, of the distinctions of a given partition of a set, an idea that can be naturally generalized to classical probability distributions. Here, we analyze how fundamental concepts…

Quantum Physics · Physics 2022-03-14 Boaz Tamir , Ismael L. Paiva , Zohar Schwartzman-Nowik , Eliahu Cohen

The new interpretation of Quantum Mechanics is based on a complex probability theory. An interpretation postulate specifies events which can be observed and it follows that the complex probability of such event is, in fact, a real positive…

Quantum Physics · Physics 2007-05-23 Jiri Soucek

There is a generic way to add any new feature to a system. It involves 1) identifying the basic units which build up the system and 2) introducing the new feature to each of these basic units. In the case where the system is argumentation…

Artificial Intelligence · Computer Science 2015-03-19 D. M. Gabbay , O. Rodrigues

We introduce Probabilistic Regular Expressions (PRE), a probabilistic analogue of regular expressions denoting probabilistic languages in which every word is assigned a probability of being generated. We present and prove the completeness…

Logic in Computer Science · Computer Science 2024-05-20 Wojciech Różowski , Alexandra Silva

The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic…

Artificial Intelligence · Computer Science 2018-03-12 Regis Riveret , Pietro Baroni , Yang Gao , Guido Governatori , Antonino Rotolo , Giovanni Sartor

In this paper, we elaborate on the ordered-pair semantics originally presented by Matthew Clemens for LP (Priest's Logic of Paradox). For this purpose, we build on a generalization of Clemens semantics to the case of n-tuple semantics, for…

Logic in Computer Science · Computer Science 2025-01-03 Hitoshi Omori , Jonas R. B. Arenhart

This is the logical foundation for for Relativity Theory, Probability Theory, and for Quantum Theory. Contents is the following: 1 Introduction. 2 Classical logic. 3 Time and space. 3.1 Recorders. 3.2 Time. 3.3 Space. 3.4 Relativity. 4.…

General Physics · Physics 2007-05-23 G. A. Quznetsov
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