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This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the…

Artificial Intelligence · Computer Science 2013-03-08 Salem Benferhat , Didier Dubois , Henri Prade

Mathematical proofs are often said to justify their conclusions by indicating the existence of a corresponding formal derivation. We argue that this widespread view relies on an under-examined notion of correspondence, or what it means for…

History and Overview · Mathematics 2026-03-20 Simon DeDeo , Eamon Duede

Recent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks and social media. Analytics in terms of defeasible reasoning - for example for decision making - could provide…

Logic in Computer Science · Computer Science 2021-02-16 Michael J. Maher , Ilias Tachmazidis , Grigoris Antoniou , Stephen Wade , Long Cheng

Language technologies that accurately model the dynamics of events must perform commonsense reasoning. Existing work evaluating commonsense reasoning focuses on making inferences about common, everyday situations. To instead investigate the…

Computation and Language · Computer Science 2024-05-02 Wenting Zhao , Justin T Chiu , Jena D. Hwang , Faeze Brahman , Jack Hessel , Sanjiban Choudhury , Yejin Choi , Xiang Lorraine Li , Alane Suhr

The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic…

Artificial Intelligence · Computer Science 2018-03-12 Regis Riveret , Pietro Baroni , Yang Gao , Guido Governatori , Antonino Rotolo , Giovanni Sartor

With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts to account for the major variation in prediction. Yet,…

Machine Learning · Computer Science 2023-09-12 Wenbo Zhang , Tong Wu , Yunlong Wang , Yong Cai , Hengrui Cai

There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to make their algorithms more understandable. Much of this research is focused on explicitly explaining decisions or…

Artificial Intelligence · Computer Science 2018-08-16 Tim Miller

In many instances in first order logic or computable algebra, classical theorems show that many problems are undecidable for general structures, but become decidable if some rigidity is imposed on the structure. For example, the set of…

Discrete Mathematics · Computer Science 2017-08-08 Emmanuel Jeandel

Informal logic is a method of argument analysis which is complementary to that of formal logic, providing for the pragmatic treatment of features of argumentation which cannot be reduced to logical form. The central claim of this paper is…

History and Overview · Mathematics 2019-05-03 Andrew Aberdein

Defeasible logics provide several linguistic features to support the expression of defeasible knowledge. There is also a wide variety of such logics, expressing different intuitions about defeasible reasoning. However, the logics can only…

Logic in Computer Science · Computer Science 2021-02-16 Guido Governatori , Michael J. Maher

Given a classification model and a prediction for some input, there are heuristic strategies for ranking features according to their importance in regard to the prediction. One common approach to this task is rooted in propositional logic…

Artificial Intelligence · Computer Science 2025-05-16 Tomás Capdevielle , Santiago Cifuentes

This thesis is concerned with investigations into the "complexity of term rewriting systems". Moreover the majority of the presented work deals with the "automation" of such a complexity analysis. The aim of this introduction is to present…

Logic in Computer Science · Computer Science 2009-12-30 Georg Moser

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules…

Artificial Intelligence · Computer Science 2007-05-23 Alejandro Javier Garcia , Guillermo Ricardo Simari

The framework of algorithmic knowledge assumes that agents use algorithms to compute the facts they explicitly know. In many cases of interest, a deductive system, rather than a particular algorithm, captures the formal reasoning used by…

Artificial Intelligence · Computer Science 2007-05-23 Riccardo Pucella

Basic problems of complex systems are outlined with an emphasis on irreducibility and dynamic many-to-many correspondences. We discuss the importance of a constructive approach to artificial reality and the significance of an internal…

adap-org · Physics 2009-10-22 Kunihiko Kaneko , Ichiro Tsuda

Modern language models (LMs) exhibit strong deductive reasoning capabilities, yet standard evaluations emphasize correctness while overlooking a key aspect of reasoning: efficiency. In real-world reasoning scenarios, much of the available…

The study of arguments as abstract entities and their interaction as introduced by Dung (Artificial Intelligence 177, 1995) has become one of the most active research branches within Artificial Intelligence and Reasoning. A main issue for…

Artificial Intelligence · Computer Science 2011-05-16 Eun Jung Kim , Sebastian Ordyniak , Stefan Szeider

Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible…

Artificial Intelligence · Computer Science 2012-07-19 Carlos Chesnevar , Guillermo Simari , Teresa Alsinet , Lluis Godo

We explore the rational, formal and non-formal criteria of consistency, non-triviality and redundancy in the mathematical research now a days. We develop a paradigmatic discussion by analysing the different conceptions of those criteria,…

History and Overview · Mathematics 2018-03-01 Eleonora Catsigeras

Social scientists are increasingly turning to unstructured datasets to unlock new empirical insights, e.g., estimating descriptive statistics of or causal effects on quantitative measures derived from text, audio, or video data. In many…

Econometrics · Economics 2026-05-06 Jacob Carlson