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Plausible reasoning concerns situations whose inherent lack of precision is not quantified; that is, there are no degrees or levels of precision, and hence no use of numbers like probabilities. A hopefully comprehensive set of principles…

Artificial Intelligence · Computer Science 2017-04-05 David Billington

Modal logic is a paradigm for several useful and applicable formal systems in computer science. It generally retains the low complexity of classical propositional logic, but notable exceptions exist in the domains of description, temporal,…

Logic in Computer Science · Computer Science 2016-09-15 Davide Bresolin , Emilio Muñoz-Velasco , Guido Sciavicco

Given the large variety of existing logical formalisms it is of utmost importance to select the most adequate one for a specific purpose, e.g. for representing the knowledge relevant for a particular application or for using the formalism…

Artificial Intelligence · Computer Science 2020-03-04 Ringo Baumann

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

The paper describes an extension of well-founded semantics for logic programs with two types of negation. In this extension information about preferences between rules can be expressed in the logical language and derived dynamically. This…

Artificial Intelligence · Computer Science 2008-02-03 G. Brewka

Possibility theory offers a framework where both Lehmann's "preferential inference" and the more productive (but less cautious) "rational closure inference" can be represented. However, there are situations where the second inference does…

Artificial Intelligence · Computer Science 2013-02-18 Salem Benferhat , Didier Dubois , Henri Prade

Prioritized default reasoning has illustrated its rich expressiveness and flexibility in knowledge representation and reasoning. However, many important aspects of prioritized default reasoning have yet to be thoroughly explored. In this…

Artificial Intelligence · Computer Science 2007-05-23 Yan Zhang

Languages may encode similar meanings using different sentence structures. This makes it a challenge to provide a single set of formal rules that can derive meanings from sentences in many languages at once. To overcome the challenge, we…

Computation and Language · Computer Science 2024-03-05 Laurestine Bradford , Timothy John O'Donnell , Siva Reddy

The classical propositional logic is known to be sound and complete with respect to the set semantics that interprets connectives as set operations. The paper extends propositional language by a new binary modality that corresponds to…

Logic in Computer Science · Computer Science 2007-05-23 Pavel Naumov

Applying dynamic logics to program verifications is a challenge, because their axiomatic rules for regular expressions can be difficult to be adapted to different program models. We present a novel dynamic logic, called DLp, which supports…

Logic in Computer Science · Computer Science 2026-02-11 Yuanrui Zhang

Recent ideas about epistemic modals and indicative conditionals in formal semantics have significant overlap with ideas in modal logic and dynamic epistemic logic. The purpose of this paper is to show how greater interaction between formal…

Logic in Computer Science · Computer Science 2017-08-07 Wesley H. Holliday , Thomas F. Icard

This paper introduces modal independence logic MIL, a modal logic that can explicitly talk about independence among propositional variables. Formulas of MIL are not evaluated in worlds but in sets of worlds, so called teams. In this vein,…

Logic in Computer Science · Computer Science 2014-04-02 Juha Kontinen , Julian-Steffen Müller , Henning Schnoor , Heribert Vollmer

The search for information on the web is faced with several problems, which arise on the one hand from the vast number of available sources, and on the other hand from their heterogeneity. A promising approach is the use of multi-agent…

Multiagent Systems · Computer Science 2007-05-23 T. Eiter , M. Fink , G. Sabbatini , H. Tompits

Intuitionistic Propositional Logic is proved to be an infinitely many valued logic by Kurt G\"odel (1932), and it is proved by Stanis{\l}aw Ja\'skowski (1936) to be a countably many valued logic. In this paper, we provide alternative proofs…

Logic · Mathematics 2021-11-30 Saeed Salehi

Proofs, in Ludics, have an interpretation provided by their counter-proofs, that is the objects they interact with. We follow the same idea by proposing that sentence meanings are given by the counter-meanings they are opposed to in a…

Computation and Language · Computer Science 2009-10-09 Alain Lecomte , Myriam Quatrini

In this paper, we study a new Kripke-style semantics for classical modal logic, named as provability models. We study provability models for the propositional modal logics K, K4, S4 GL, GLP and the interpretability logic ILM. Provability…

Logic · Mathematics 2025-11-20 Mojtaba Mojtahedi , Borja Sierra Miranda

Inclusion logic is a variant of dependence logic that was shown to have the same expressive power as positive greatest fixed-point logic. Inclusion logic is not axiomatizable in full, but its first-order consequences can be axiomatized. In…

Logic · Mathematics 2020-01-22 Fan Yang

We define a fragment of propositional logic where isomorphic propositions, such as $A\land B$ and $B\land A$, or $A\Rightarrow (B\land C)$ and $(A\Rightarrow B)\land(A\Rightarrow C)$ are identified. We define System I, a proof language for…

Logic in Computer Science · Computer Science 2019-12-06 Alejandro Díaz-Caro , Gilles Dowek

Argumentation is one of the most popular approaches of defining a~non-monotonic formalism and several argumentation based semantics were proposed for defeasible logic programs. Recently, a new approach based on notions of conflict…

Artificial Intelligence · Computer Science 2014-04-29 Jozef Frtús

Large language models (LLMs) have emerged as powerful tools for many AI problems and exhibit remarkable in-context learning (ICL) capabilities. Compositional ability, solving unseen complex tasks that combine two or more simple tasks, is an…

Computation and Language · Computer Science 2024-08-13 Zhuoyan Xu , Zhenmei Shi , Yingyu Liang
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