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Related papers: Rational Nonmonotonic Reasoning

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One advantage of paraconsistent logic is that it can deal with inconsistencies without making the system trivial. However, unlike classical propositional calculus, its deductive system is limited, and the meaning of paraconsistent negation…

Logic · Mathematics 2025-10-14 Oscar Ramírez

Possibilistic logic, an extension of first-order logic, deals with uncertainty that can be estimated in terms of possibility and necessity measures. Syntactically, this means that a first-order formula is equipped with a possibility degree…

Artificial Intelligence · Computer Science 2013-02-28 Bernhard Hollunder

Recent scholarship on reasoning in LLMs has supplied evidence of impressive performance and flexible adaptation to machine generated or human feedback. Nonmonotonic reasoning, crucial to human cognition for navigating the real world,…

Computation and Language · Computer Science 2024-06-13 Alina Leidinger , Robert van Rooij , Ekaterina Shutova

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk…

Theoretical Economics · Economics 2020-08-11 Christian Tarsney

Fuzziness and randomicity widespread exist in natural science, engineering, technology and social science. The purpose of this paper is to present a new logic - uncertain propositional logic which can deal with both fuzziness by taking…

Logic · Mathematics 2015-06-11 Maokang Luo , Wei He

This paper presents an extension of Defeasible Deontic Logic to deal with the Pragmatic Oddity problem. The logic applies three general principles: (1) the Pragmatic Oddity problem must be solved within a general logical treatment of CTD…

Logic in Computer Science · Computer Science 2022-09-13 Guido Governatori , Silvano Colombo Tosatto , Antonino Rotolo

We present a uniform non-monotonic solution to the problems of reasoning about action on the basis of an argumentation-theoretic approach. Our theory is provably correct relative to a sensible minimisation policy introduced on top of a…

Artificial Intelligence · Computer Science 2011-09-13 N. Y. Foo , Q. B. Vo

In this paper, we provide more evidence for the contention that logical consequence should be understood in normative terms. Hartry Field and John MacFarlane covered the classical case. We extend their work, examining what it means for an…

Logic in Computer Science · Computer Science 2014-02-20 Julio Lemos

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

We present the language {m P}{cal C}+ for probabilistic reasoning about actions, which is a generalization of the action language {cal C}+ that allows to deal with probabilistic as well as nondeterministic effects of actions. We define a…

Artificial Intelligence · Computer Science 2012-12-12 Thomas Eiter , Thomas Lukasiewicz

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

W.C. Rounds and G.-Q. Zhang (2001) have proposed to study a form of disjunctive logic programming generalized to algebraic domains. This system allows reasoning with information which is hierarchically structured and forms a (suitable)…

Artificial Intelligence · Computer Science 2007-05-23 Pascal Hitzler

Tremendous research effort has been dedicated over the years to thoroughly investigate non-monotonic reasoning. With the abundance of non-monotonic logical formalisms, a unified theory that enables comparing the different approaches is much…

Logic in Computer Science · Computer Science 2019-07-23 Nourhan Ehab , Haythem O. Ismail

Based on ideas of quantum theory of open systems and psychological dual system theory we propose two novel versions of Non-Boolean logic. The first version can be interpreted in our opinion as simplified description of primitive…

Neurons and Cognition · Quantitative Biology 2015-09-29 E. D. Vol

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

Temporal commonsense reasoning refers to the ability to understand the typical temporal context of phrases, actions, and events, and use it to reason over problems requiring such knowledge. This trait is essential in temporal natural…

Artificial Intelligence · Computer Science 2023-11-17 Georg Wenzel , Adam Jatowt

Neural rationale models are popular for interpretable predictions of NLP tasks. In these, a selector extracts segments of the input text, called rationales, and passes these segments to a classifier for prediction. Since the rationale is…

Computation and Language · Computer Science 2022-07-26 Yiming Zheng , Serena Booth , Julie Shah , Yilun Zhou

Standpoint logics offer unified modal logic-based formalisms for representing multiple heterogeneous viewpoints. At the same time, many non-monotonic reasoning frameworks can be naturally captured using modal logics, in particular using the…

Artificial Intelligence · Computer Science 2025-11-18 Piotr Gorczyca , Hannes Strass

We present a new system S for handling uncertainty in a quantified modal logic (first-order modal logic). The system is based on both probability theory and proof theory. The system is derived from Chisholm's epistemology. We concretize…

Artificial Intelligence · Computer Science 2018-05-29 Naveen Sundar Govindarajulu , Selmer Bringsjord

Transparency is a fundamental requirement for decision making systems when these should be deployed in the real world. It is usually achieved by providing explanations of the system's behavior. A prominent and intuitive type of explanations…

Machine Learning · Computer Science 2021-07-23 André Artelt , Valerie Vaquet , Riza Velioglu , Fabian Hinder , Johannes Brinkrolf , Malte Schilling , Barbara Hammer
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