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Precedential constraint is one foundation of case-based reasoning in AI and Law. It generally assumes that the underlying set of precedents must be consistent. To relax this assumption, a generalized notion of the reason model has been…

Artificial Intelligence · Computer Science 2025-10-23 Wachara Fungwacharakorn , Gauvain Bourgne , Ken Satoh

An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained…

Artificial Intelligence · Computer Science 2020-02-19 Claudia Schulz , Francesca Toni

Argumentation Frameworks (AFs) are a key formalism in AI research. Their semantics have been investigated in terms of principles, which define characteristic properties in order to deliver guidance for analysing established and developing…

Artificial Intelligence · Computer Science 2022-05-09 Wolfgang Dvořák , Matthias König , Markus Ulbricht , Stefan Woltran

In this paper we introduce a Conditional Answer Set Programming framework (Conditional ASP) for the definition of conditional extensions of Answer Set Programming (ASP). The approach builds on a conditional logic with typicality, and on the…

Artificial Intelligence · Computer Science 2026-01-08 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

After a few decades of development, computational argumentation has become one of the active realms in AI. This paper considers extension-based concrete and abstract semantics of argumentation. For concrete ones, based on Grossi and…

Artificial Intelligence · Computer Science 2021-05-21 Lixing Tan , Zhaohui Zhu , Jinjin Zhang

This paper combines two studies: a topological semantics for epistemic notions and abstract argumentation theory. In our combined setting, we use a topological semantics to represent the structure of an agent's collection of evidence, and…

Artificial Intelligence · Computer Science 2017-07-28 Chenwei Shi , Sonja Smets , Fernando R. Velázquez-Quesada

The logic underlying the Abella proof assistant includes mechanisms for interpreting atomic predicates through fixed point definitions that can additionally be treated inductively or co-inductively. However, the original formulation of the…

Logic in Computer Science · Computer Science 2025-10-15 Nathan Guermond , Gopalan Nadathur

Answer Set Programming (ASP) is a powerful modelling formalism that is very efficient in solving combinatorial problems. ASP solvers implement the stable model semantics that eliminates circular derivations between Boolean variables from…

Artificial Intelligence · Computer Science 2014-05-15 Rehan Abdul Aziz

Over the last decade, as we rely more on deep learning technologies to make critical decisions, concerns regarding their safety, reliability and interpretability have emerged. We introduce a novel Neural Argumentative Learning (NAL)…

Machine Learning · Computer Science 2025-06-18 Abdul Rahman Jacob , Avinash Kori , Emanuele De Angelis , Ben Glocker , Maurizio Proietti , Francesca Toni

Although various aspects of soft-constraint based norms have been explored, it is still challenging to understand preemption. Preemption is a situation where higher-level norms override lower-level norms when new information emerges. To…

Artificial Intelligence · Computer Science 2024-09-09 Wachara Fungwacharakorn , Kanae Tsushima , Hiroshi Hosobe , Hideaki Takeda , Ken Satoh

This paper puts forth a class of algebraic structures, relativized Boolean algebras (RBAs), that provide semantics for propositional logic in which truth/validity is only defined relative to a local domain. In particular, the join of an…

Logic in Computer Science · Computer Science 2021-10-06 Evan Piermont

We introduce stratified labelings as a novel semantical approach to abstract argumentation frameworks. Compared to standard labelings, stratified labelings provide a more fine-grained assessment of the controversiality of arguments using…

Artificial Intelligence · Computer Science 2013-08-06 Matthias Thimm , Gabriele Kern-Isberner

This paper describes an architecture for robots that combines the complementary strengths of probabilistic graphical models and declarative programming to represent and reason with logic-based and probabilistic descriptions of uncertainty…

Robotics · Computer Science 2018-09-24 Mohan Sridharan , Michael Gelfond , Shiqi Zhang , Jeremy Wyatt

In ASPIC-style structured argumentation an argument can rebut another argument by attacking its conclusion. Two ways of formalizing rebuttal have been proposed: In restricted rebuttal, the attacked conclusion must have been arrived at with…

Artificial Intelligence · Computer Science 2020-07-10 Marcos Cramer , Meghna Bhadra

In Dung-style abstract argumentation, various semantics capture notions of acceptability of arguments. The admissibility semantics capture the notion that an argument can be consistently defended from any potential counterargument. Weak…

Artificial Intelligence · Computer Science 2026-05-05 Uri Andrews , Luca San Mauro , John Spoerl

Modelling qualitative uncertainty in formal argumentation is essential both for practical applications and theoretical understanding. Yet, most of the existing works focus on \textit{abstract} models for arguing with uncertainty. Following…

Artificial Intelligence · Computer Science 2026-02-18 Carlo Proietti , Antonio Yuste-Ginel

The recent Control Argumentation Framework (CAF) is a generalization of Dung's Argumentation Framework which handles argumentation dynamics under uncertainty; especially it can be used to model the behavior of an agent which can anticipate…

Artificial Intelligence · Computer Science 2020-09-11 Jean-Guy Mailly

Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled…

Artificial Intelligence · Computer Science 2013-03-08 John Fox , Paul J. Krause , Morten Elvang-Gøransson

Quantitative Bipolar Argumentation Frameworks (QBAFs) provide an alternative approach to computing argument acceptability in Bipolar Argumentation Frameworks (BAFs). Each argument is assigned an initial strength, which is then updated to a…

Artificial Intelligence · Computer Science 2026-05-05 Gianvincenzo Alfano , Sergio Greco , Lucio La Cava , Francesco Parisi , Irina Trubitsyna

We present an extension-based approach for computing and verifying preferences in an abstract argumentation system. Although numerous argumentation semantics have been developed previously for identifying acceptable sets of arguments from…

Artificial Intelligence · Computer Science 2024-03-27 Quratul-ain Mahesar , Nir Oren , Wamberto W. Vasconcelos