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Let L be some extension of classical propositional logic. The non-iterated probabilistic logic over L, is the logic PL that is defined by adding non-nested probabilistic operators in the language of L. For example in PL we can express a…

Logic in Computer Science · Computer Science 2019-02-12 Ioannis Kokkinis

We present a propositional logic %which can be used to reason about the uncertainty of events, where the uncertainty is modeled by a set of probability measures assigning an interval of probability to each event. We give a sound and…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

We present new results on finite satisfiability of logics with counting and arithmetic. One result is a tight bound on the complexity of satisfiability of logics with so-called local Presburger quantifiers, which sum over neighbors of a…

Logic in Computer Science · Computer Science 2025-10-31 Michael Benedikt , Chia-Hsuan Lu , Tony Tan

We involve a certain propositional logic based on ortholattices. We characterize the implicational reduct of such a logic and we show that its algebraic counterpart is the so-called orthosemilattice. Properties of congruences and congruence…

Quantum Physics · Physics 2007-05-23 I. Chajda , R. Halas

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The…

Artificial Intelligence · Computer Science 2013-03-26 Jerome Lang , Didier Dubois , Henri Prade

We define an extension of predicate logic, called Binding Logic, where variables can be bound in terms and in propositions. We introduce a notion of model for this logic and prove a soundness and completeness theorem for it. This theorem is…

Logic in Computer Science · Computer Science 2023-05-26 Gilles Dowek , Thérèse Hardin , Claude Kirchner

The infinitary propositional logic of here-and-there is important for the theory of answer set programming in view of its relation to strongly equivalent transformations of logic programs. We know a formal system axiomatizing this logic…

Logic in Computer Science · Computer Science 2016-08-05 Amelia Harrison , Vladimir Lifschitz , Julian Michael

The purpose of this paper is to introduce justification logics based on conditional logics. We introduce a new family of logics, called conditional justification logics, which incorporates a counterfactual conditional in its language. For…

Logic · Mathematics 2025-01-17 Meghdad Ghari

Based on an analysis of the inference rules used, we provide a characterization of the situations in which classical provability entails intuitionistic provability. We then examine the relationship of these derivability notions to uniform…

Logic in Computer Science · Computer Science 2016-08-31 Gopalan Nadathur

We obtain, for the first time, a modular many-valued semantics for combined logics, which is built directly from many-valued semantics for the logics being combined, by means of suitable universal operations over partial non-deterministic…

Logic · Mathematics 2024-05-22 Carlos Caleiro , Sérgio Marcelino

Given a consequence relation in many-valued logic, what connectives can be defined? For instance, does there always exist a conditional operator internalizing the consequence relation, and which form should it take? In this paper, we pose…

Logic · Mathematics 2019-07-26 Emmanuel Chemla , Paul Egré

A $\lambda$-calculus is introduced in which all programs can be evaluated in probabilistic polynomial time and in which there is sufficient structure to represent sequential cryptographic constructions and adversaries for them, even when…

Programming Languages · Computer Science 2024-10-24 Ugo Dal Lago , Zeinab Galal , Giulia Giusti

We establish a criterion to decide when a countable projective limit of countable inductive limits of normed spaces is bornological. We compare the conditions occurring within our criterion with well-known abstract conditions from the…

Functional Analysis · Mathematics 2014-06-30 José Bonet , Sven-Ake Wegner

A logic is defined that allows to express information about statistical probabilities and about degrees of belief in specific propositions. By interpreting the two types of probabilities in one common probability space, the semantics given…

Artificial Intelligence · Computer Science 2013-02-28 Manfred Jaeger

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

Incorporating constraints is a major concern in probabilistic machine learning. A wide variety of problems require predictions to be integrated with reasoning about constraints, from modelling routes on maps to approving loan predictions.…

Machine Learning · Computer Science 2020-01-31 Ioannis Papantonis , Vaishak Belle

The theory of probability and the quantum theory, the one mathematical and the other physical, are related in that each admits a number of very different interpretations. It has been proposed that the conceptual problems of the quantum…

Quantum Physics · Physics 2021-08-29 Louis Marchildon

We discuss combinatorial conditions for the existence of various types of reductions between equivalence relations, and in particular identify necessary and sufficient conditions for the existence of injective reductions.

Logic · Mathematics 2014-10-29 Dan Hathaway , Scott Schneider

We show that Morley's theorem on the number of countable models of a countable first-order theory becomes an undecidable statement when extended to second-order logic. More generally, we calculate the number of equivalence classes of…

Logic · Mathematics 2023-07-06 Christopher J. Eagle , Clovis Hamel , Sandra Müller , Franklin D. Tall

We present a propositional logic to reason about the uncertainty of events, where the uncertainty is modeled by a set of probability measures assigning an interval of probability to each event. We give a sound and complete axiomatization…

Artificial Intelligence · Computer Science 2014-08-08 Joseph Y. Halpern , Riccardo Pucella