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The language of probability is used to define several different types of conditional statements. There are four principal types: subjunctive, material, existential, and feasibility. Two further types of conditionals are defined using the…

Logic · Mathematics 2014-09-29 Joseph W. Norman

The process of doing Science in condition of uncertainty is illustrated with a toy experiment in which the inferential and the forecasting aspects are both present. The fundamental aspects of probabilistic reasoning, also relevant in real…

History and Overview · Mathematics 2018-02-07 Giulio D'Agostini

To operate intelligently in the world, an agent must reason about its actions. The consequences of an action are a function of both the state of the world and the action itself. Many aspects of the world are inherently stochastic, so a…

Artificial Intelligence · Computer Science 2013-04-05 Peter Haddawy

Prediction sets offer a binary inclusion/exclusion for each element at the same fixed confidence level. We generalize to fuzzy prediction sets, which exclude elements at their own data-driven confidence level. Our key insight is that a…

Statistics Theory · Mathematics 2026-04-01 Nick W. Koning , Sam van Meer

Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. A purely numeric mechanism, like those proposed so far, cannot provide a…

Artificial Intelligence · Computer Science 2013-04-15 Alan Bundy

This paper presents an approach for developing the explanation capabilities of rule-based expert systems managing imprecise and uncertain knowledge. The treatment of uncertainty takes place in the framework of possibility theory where the…

Artificial Intelligence · Computer Science 2013-04-08 Henri Farrency , Henri Prade

A review is presented of the correspondence existing in both classical bivalent logic (BL) and canonical fuzzy logic (CFL) between each law or tautology in propositional calculus and a law in set theory. The latter law consists of the…

General Mathematics · Mathematics 2023-03-13 Osvaldo Skliar , Sherry Gapper , Ricardo E. Monge

In this paper, we present the interval neutrosophic logics which generalizes the fuzzy logic, paraconsistent logic, intuitionistic fuzzy logic and many other non-classical and non-standard logics. We will give the formal definition of…

Logic in Computer Science · Computer Science 2007-05-23 Haibin Wang , Florentin Smarandache , Yanqing Zhang , Rajshekhar Sunderraman

We use princiles of fuzzy logic to develop a general model representing several processes in a system's operation characterized by a degree of vagueness and/or uncertainy. Further, we introduce three altenative measures of a fuzzy system's…

Artificial Intelligence · Computer Science 2012-12-12 Michael Gr. Voskoglou

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

Modal probabilistic logics provide a framework for reasoning about probability in modal contexts, involving notions such as knowledge, belief, time, and action. In this paper, we study a particular family of these logics, extending the…

Logic in Computer Science · Computer Science 2025-12-01 Daniil Kozhemiachenko , Igor Sedlár

This paper is an extended version of an earlier submission to WoLLIC 2023. We discuss two-layered logics formalising reasoning with probabilities and belief functions that combine the Lukasiewicz $[0,1]$-valued logic with Baaz $\triangle$…

Logic · Mathematics 2025-05-20 Marta Bilkova , Sabine Frittella , Daniil Kozhemiachenko , Ondrej Majer

Probabilistic separation logic offers an approach to reasoning about imperative probabilistic programs in which a separating conjunction is used as a mechanism for expressing independence properties. Crucial to the effectiveness of the…

Logic in Computer Science · Computer Science 2026-03-03 Janez Ignacij Jereb , Alex Simpson

Probabilistic Soft Logic has been proposed and used in several applications as an efficient way to deal with inconsistency, uncertainty and relational representation. In several applications, this approach has led to an adequate description…

Logic in Computer Science · Computer Science 2016-11-22 Vladik Kreinovich , Chitta Baral

This paper addresses the problem of merging uncertain information in the framework of possibilistic logic. It presents several syntactic combination rules to merge possibilistic knowledge bases, provided by different sources, into a new…

Artificial Intelligence · Computer Science 2013-02-01 Salem Benferhat , Claudio Sossai

This paper argues for a modal view of probability. The syntax and semantics of one particularly strong probability logic are discussed and some examples of the use of the logic are provided. We show that it is both natural and useful to…

Artificial Intelligence · Computer Science 2013-04-10 Alan M. Frisch , Peter Haddawy

Communicating forecast uncertainty effectively is a persistent challenge in predictive endeavours such as weather forecasting. This paper explores the application of possibility theory as a complementary approach to traditional probability…

Applications · Statistics 2024-10-30 John R. Lawson

Many representation schemes combining first-order logic and probability have been proposed in recent years. Progress in unifying logical and probabilistic inference has been slower. Existing methods are mainly variants of lifted variable…

Artificial Intelligence · Computer Science 2012-02-20 Vibhav Gogate , Pedro Domingos

According to quantum mechanics, statements about the future made by sentient beings like us are, in general, neither true nor false; they must satisfy a many-valued logic. I propose that the truth value of such a statement should be…

Quantum Physics · Physics 2017-10-24 Anthony Sudbery

Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical systems for formalizing such reasoning, even when the language for expressing uncertainty is the same. In the case of reasoning about…

Artificial Intelligence · Computer Science 2021-04-07 Matthew Harrison-Trainor , Wesley H. Holliday , Thomas F. Icard
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