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We design an expansion of Belnap--Dunn logic with belief and plausibility functions that allow non-trivial reasoning with inconsistent and incomplete probabilistic information. We also formalise reasoning with non-standard probabilities and…

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

We propose an integration of possibility theory into non-classical logics. We obtain many formal results that generalize the case where possibility and necessity functions are based on classical logic. We show how useful such an approach is…

Artificial Intelligence · Computer Science 2013-02-28 Philippe Besnard , Jerome Lang

We combine the concepts of modal logics and many-valued logics in a general and comprehensive way. Namely, given any finite linearly ordered set of truth values and any set of propositional connectives defined by truth tables, we define the…

Logic in Computer Science · Computer Science 2025-01-03 Amir Karniel , Michael Kaminski

Possibilistic logic has been proposed as a numerical formalism for reasoning with uncertainty. There has been interest in developing qualitative accounts of possibility, as well as an explanation of the relationship between possibility and…

Artificial Intelligence · Computer Science 2013-03-25 Craig Boutilier

This paper belongs to the field of probabilistic modal logic, focusing on a comparative analysis of two distinct semantics: one rooted in Kripke semantics and the other in neighbourhood semantics. The primary distinction lies in the…

Logic · Mathematics 2024-04-25 Nino Guallart

Modal logics for reasoning about the power of coalitions capture the notion of effectivity functions associated with game forms. The main goal of coalition logics is to provide formal tools for modeling the dynamics of a game frame whose…

Logic · Mathematics 2017-03-01 Tomáš Kroupa , Bruno Teheux

Within the possibilistic approach to uncertainty modeling, the paper presents a modal logical system to reason about qualitative (comparative) statements of the possibility (and necessity) of fuzzy propositions. We relate this qualitative…

Logic in Computer Science · Computer Science 2013-02-28 Petr Hajek , Dagmar Harmancová , Francesc Esteva , Pere Garcia , Lluis Godo

Belief and plausibility are weaker measures of uncertainty than that of probability. They are motivated by the situations when full probabilistic information is not available. However, information can also be contradictory. Therefore, the…

Artificial Intelligence · Computer Science 2022-05-31 Sabine Frittella , Ondrej Majer , Sajad Nazari

This paper addresses fundamental issues on the nature of the concepts and structures of fuzzy logic, focusing, in particular, on the conceptual and functional differences that exist between probabilistic and possibilistic approaches. A…

Artificial Intelligence · Computer Science 2013-04-05 Enrique H. Ruspini

We define a family of intuitionistic non-normal modal logics; they can bee seen as intuitionistic counterparts of classical ones. We first consider monomodal logics, which contain only one between Necessity and Possibility. We then consider…

Logic in Computer Science · Computer Science 2019-01-30 Tiziano Dalmonte , Charles Grellois , Nicola Olivetti

While belief functions may be seen formally as a generalization of probabilistic distributions, the question of the interactions between belief functions and probability is still an issue in practice. This question is difficult, since the…

Logic in Computer Science · Computer Science 2011-10-03 Frederic Dambreville

A primary motivation for reasoning under uncertainty is to derive decisions in the face of inconclusive evidence. However, Shafer's theory of belief functions, which explicitly represents the underconstrained nature of many reasoning…

Artificial Intelligence · Computer Science 2013-04-08 Thomas M. Strat

This paper relates comparative belief structures and a general view of belief management in the setting of deductively closed logical representations of accepted beliefs. We show that the range of compatibility between the classical…

Artificial Intelligence · Computer Science 2013-02-01 Didier Dubois , Helene Fargier , Henri Prade

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

This paper develops the model theory of normal modal logics based on partial "possibilities" instead of total "worlds," following Humberstone (1981) instead of Kripke (1963). Possibility semantics can be seen as extending to modal logic the…

Logic · Mathematics 2025-01-22 Wesley H. Holliday

This paper considers the notion of possible events which are insignificant in probabilistic analysis (i.e. events that have zero probability). The paper discusses the method of modal logic based on "possible worlds" and discusses a…

Other Statistics · Statistics 2022-11-08 Ben O'Neill

We explore a fuzzy modal logic that can formalise probabilistic reasoning about actions and knowledge. In particular, we deal with contexts involving statements about events expressed via modal formulas, e.g., "after doing $a$, the…

Logic in Computer Science · Computer Science 2026-04-27 Daniil Kozhemiachenko , Igor Sedlár

Propositional term modal logic is interpreted over Kripke structures with unboundedly many accessibility relations and hence the syntax admits variables indexing modalities and quantification over them. This logic is undecidable, and we…

Logic in Computer Science · Computer Science 2019-01-01 Anantha Padmanabha , R Ramanujam

Plausibility models are Kripke models that agents use to reason about knowledge and belief, both of themselves and of each other. Such models are used to interpret the notions of conditional belief, degrees of belief, and safe belief. The…

Artificial Intelligence · Computer Science 2018-02-06 Mikkel Birkegaard Andersen , Thomas Bolander , Hans van Ditmarsch , Martin Holm Jensen
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