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Related papers: Quantified preference logic

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Classical Decision Theory provides a normative framework for representing and reasoning about complex preferences. Straightforward application of this theory to automate decision making is difficult due to high elicitation cost. In response…

Artificial Intelligence · Computer Science 2013-01-30 Vu A. Ha , Peter Haddawy

Our objective in this note is to comment briefly on the newly emerging literature on computer-aided proofs in Social Choice Theory. We shall specifically comment on two papers, one by Tang and Lin (2009) and another by Geist and Endriss…

Logic in Computer Science · Computer Science 2014-03-17 Siddharth Chatterjee , Arunava Sen

The well-quasi-orders (WQO) play an important role in various fields such as Computer Science, Logic or Graph Theory. Since the class of WQOs lacks closure under some important operations, the proof that a certain quasi-order is WQO…

Logic · Mathematics 2024-10-18 Yann Pequignot

Algebraic logic studies algebraic theories related to proposition and first-order logic. A new algebraic approach to first-order logic is sketched in this paper. We introduce the notion of a quantifier theory, which is a functor from the…

Logic in Computer Science · Computer Science 2013-01-07 Zhaohua Luo

In response to a concern raised by Horty, this paper develops a two-tiered, preference-based semantic framework for modeling defeasible conditional obligations. The paper extends a Hansson-Lewis style preference semantics for dyadic deontic…

Logic in Computer Science · Computer Science 2026-05-01 Xavier Parent

Probability theory as extended logic is completed such that essentially any probability may be determined. This is done by considering propositional logic (as opposed to predicate logic) as syntactically suffcient and imposing a symmetry…

Statistics Theory · Mathematics 2014-08-12 Cael L. Hasse

We study the logic obtained by endowing the language of first-order arithmetic with second-order measure quantifiers. This new kind of quantification allows us to express that the argument formula is true in a certain portion of all…

Logic in Computer Science · Computer Science 2021-04-27 Melissa Antonelli , Ugo Dal Lago , Paolo Pistone

In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences with Abstract Argumentation and Case-Based Reasoning (CBR).…

Artificial Intelligence · Computer Science 2024-08-06 Adam Gould , Guilherme Paulino-Passos , Seema Dadhania , Matthew Williams , Francesca Toni

We introduce a new logic that combines Adjoint Logic with Graded Necessity Modalities. This results in a very expressive system capable of controlling when and how structural rules are used. We give a sequent calculus, natural deduction,…

Logic in Computer Science · Computer Science 2020-06-17 Harley Eades , Dominic Orchard

We consider an extension of first-order logic with a recursion operator that corresponds to allowing formulas to refer to themselves. We investigate the obtained language under two different systems of semantics, thereby obtaining two…

Logic · Mathematics 2022-07-18 Reijo Jaakkola , Antti Kuusisto

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

This paper presents a plausible reasoning system to illustrate some broad issues in knowledge representation: dualities between different reasoning forms, the difficulty of unifying complementary reasoning styles, and the approximate nature…

Artificial Intelligence · Computer Science 2013-03-26 Wray L. Buntine

Argumentation is a promising model for reasoning with uncertain knowledge. The key concept of acceptability enables to differentiate arguments and counterarguments: The certainty of a proposition can then be evaluated through the most…

Artificial Intelligence · Computer Science 2013-02-01 Leila Amgoud , Claudette Cayrol

This paper investigates the possibility of performing automated reasoning in probabilistic logic when probabilities are expressed by means of linguistic quantifiers. Each linguistic term is expressed as a prescribed interval of proportions.…

Artificial Intelligence · Computer Science 2013-03-25 Didier Dubois , Henri Prade , Lluis Godo , Ramon Lopez de Mantaras

The consideration of nonstandard models of the real numbers and the definition of a qualitative ordering on those models provides a generalization of the principle of maximization of expected utility. It enables the decider to assign…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

Quantification is well known to be a major obstacle in the construction of a probabilistic network, especially when relying on human experts for this purpose. The construction of a qualitative probabilistic network has been proposed as an…

Artificial Intelligence · Computer Science 2013-01-07 Silja Renooij , Linda C. van der Gaag

In this paper we extend the predicate logic introduced in [Beauquier et al. 2002] in order to deal with Semi-Markov Processes. We prove that with respect to qualitative probabilistic properties, model checking is decidable for this logic…

Logic in Computer Science · Computer Science 2007-05-23 Ruggero Lanotte , Daniele Beauquier

A structure called a decision making problem is considered. The set of outcomes (consequences) is partially ordered according to the decision maker's preferences. The problem is how these preferences affect a decision maker to prefer one of…

Category Theory · Mathematics 2007-05-23 Victor V. Rozen , Grigori Zhitomirski

The aim of this paper is to propose a many-valued modal framework to formalize reasoning with both graded preferences and propositions, in the style of van Benthem et al.'s classical modal logics for preferences. To do so, we start from Bou…

Logic in Computer Science · Computer Science 2019-11-18 Amanda Vidal , Francesc Esteva , Lluis Godo

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
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