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Related papers: Non-monotonic Reasoning in Deductive Argumentation

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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

Recently, several approaches to updating knowledge bases modeled as extended logic programs have been introduced, ranging from basic methods to incorporate (sequences of) sets of rules into a logic program, to more elaborate methods which…

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

The use of meta-rules in logic, i.e., rules whose content includes other rules, has recently gained attention in the setting of non-monotonic reasoning: a first logical formalisation and efficient algorithms to compute the (meta)-extensions…

Artificial Intelligence · Computer Science 2022-09-27 Francesco Olivieri , Guido Governatori , Matteo Cristani , Antonino Rotolo , Abdul Sattar

(l) I have enough evidence to render the sentence S probable. (la) So, relative to what I know, it is rational of me to believe S. (2) Now that I have more evidence, S may no longer be probable. (2a) So now, relative to what I know, it is…

Artificial Intelligence · Computer Science 2016-11-26 Henry E. Kyburg

Stereotypical reasoning assumes that the situation at hand is one of a kind and that it enjoys the properties generally associated with that kind of situation. It is one of the most basic forms of nonmonotonic reasoning. A formal model for…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

One main goal of argumentation theory is to evaluate arguments and to determine whether they should be accepted or rejected. When there is no clear answer, a third option, being undecided, has to be taken into account. Indecision is often…

Artificial Intelligence · Computer Science 2022-03-07 Daniela Schuster

In many real-life settings, agents must navigate dynamic environments while reasoning under incomplete information and acting on a corpus of unstable, context-dependent, and often conflicting norms. We introduce a general, non-modal,…

Logic in Computer Science · Computer Science 2025-12-23 Mario Piazza , Andrea Sabatini

Attempts to replicate probabilistic reasoning in expert systems have typically overlooked a critical ingredient of that process. Probabilistic analysis typically requires extensive judgments regarding interdependencies among hypotheses and…

Artificial Intelligence · Computer Science 2013-04-15 Marvin S. Cohen

The paper studies defeasible reasoning in rule-based systems, in particular about legal norms and contracts. We identify rule modifiers that specify how rules interact and how they can be overridden. We then define rule transformations that…

Artificial Intelligence · Computer Science 2022-05-17 How Khang Lim , Avishkar Mahajan , Martin Strecker , Meng Weng Wong

In this paper we introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the information is possible, and where revision strategies can…

Artificial Intelligence · Computer Science 2007-05-23 Gerhard Brewka

Translations between different nonmonotonic formalisms always have been an important topic in the field, in particular to understand the knowledge-representation capabilities those formalisms offer. We provide such an investigation in terms…

Artificial Intelligence · Computer Science 2014-01-17 Wolfgang Dvorak , Stefan Woltran

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

This paper presents Abduction and Argumentation as two principled forms for reasoning, and fleshes out the fundamental role that they can play within Machine Learning. It reviews the state-of-the-art work over the past few decades on the…

Artificial Intelligence · Computer Science 2020-10-27 Antonis Kakas , Loizos Michael

We extend the $ASPIC^+$ framework for structured argumentation so as to allow applications of the reasoning by cases inference scheme for defeasible arguments. Given an argument with conclusion `$A$ or $B$', an argument based on $A$ with…

Artificial Intelligence · Computer Science 2017-03-27 Mathieu Beirlaen , Jesse Heyninck , Christian Straßer

Default logic encounters some conceptual difficulties in representing common sense reasoning tasks. We argue that we should not try to formulate modular default rules that are presumed to work in all or most circumstances. We need to take…

Artificial Intelligence · Computer Science 2013-02-08 Choh Man Teng

Tarski gave a general semantics for deductive reasoning: a formula a may be deduced from a set A of formulas iff a holds in all models in which each of the elements of A holds. A more liberal semantics has been considered: a formula a may…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

We study properties related to relevance in non-monotonic consequence relations obtained by systems of structured argumentation. Relevance desiderata concern the robustness of a consequence relation under the addition of irrelevant…

Artificial Intelligence · Computer Science 2020-05-15 AnneMarie Borg , Christian Straßer

We present a sequent calculus system for a modal reformulation of a system of nonmonotonic logic due to McCain and Turner: we prove cut elimination for our system. The proof system is in general infinitary: because we can prove cut…

Logic · Mathematics 2008-01-29 Graham White

The paper introduces a basic logic of knowledge and abduction by extending Levesque logic of only-knowing with an abduction modal operator defined via the combination of basic epistemic concepts. The upshot is an alternative approach to…

Artificial Intelligence · Computer Science 2026-01-09 Sanderson Molick , Vaishak Belle

An inductive logic can be formulated in which the elements are not propositions or probability distributions, but information systems. The logic is complete for information systems with binary hypotheses, i.e., it applies to all such…

Artificial Intelligence · Computer Science 2013-04-11 Norman C. Dalkey