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Related papers: A Comment on Argumentation

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In this paper, we discuss necessary and sufficient explanations for formal argumentation - the question whether and why a certain argument can be accepted (or not) under various extension-based semantics. Given a framework with which…

Artificial Intelligence · Computer Science 2020-11-05 AnneMarie Borg , Floris Bex

Justification theory is a unifying framework for semantics of non-monotonic logics. It is built on the notion of a justification, which intuitively is a graph that explains the truth value of certain facts in a structure. Knowledge…

Logic in Computer Science · Computer Science 2019-05-16 Simon Marynissen

In inductive learning of a broad concept, an algorithm should be able to distinguish concept examples from exceptions and noisy data. An approach through recursively finding patterns in exceptions turns out to correspond to the problem of…

Logic in Computer Science · Computer Science 2017-07-11 Farhad Shakerin , Elmer Salazar , Gopal Gupta

There are various interesting semantics' (extensions) designed for argumentation frameworks. They enable to assign a meaning, e.g., to odd-length cycles. Our main motivation is to transfer semantics' proposed by Baroni, Giacomin and Guida…

Logic in Computer Science · Computer Science 2011-08-29 Monika Adamova , Jan Sefranek

This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of…

Artificial Intelligence · Computer Science 2018-04-19 Sanjay Modgil , Henry Prakken

Reiter's original definition of default logic allows for the application of a default that contradicts a previously applied one. We call failure this condition. The possibility of generating failures has been in the past considered as a…

Artificial Intelligence · Computer Science 2021-04-12 Paolo Liberatore

We propose a novel approach to logic-based learning which generates assumption-based argumentation (ABA) frameworks from positive and negative examples, using a given background knowledge. These ABA frameworks can be mapped onto logic…

Artificial Intelligence · Computer Science 2023-05-26 Maurizio Proietti , Francesca Toni

In this paper we make a contribution to the unification of formal models of defeasible reasoning. We present several translations between formal argumentation frameworks and nonmonotonic logics for reasoning with plausible assumptions. More…

Artificial Intelligence · Computer Science 2016-04-04 Jesse Heyninck , Christian Straßer

Often, we assume that an action is permitted simply because it is not explicitly forbidden; or, similarly, that an action is forbidden simply because it is not explicitly permitted. This kind of assumptions appear, e.g., in autonomous…

Logic in Computer Science · Computer Science 2019-07-23 Pablo F. Castro , Valentin Cassano , Raul Fervari , Carlos Areces

Humans currently use arguments for explaining choices which are already made, or for evaluating potential choices. Each potential choice has usually pros and cons of various strengths. In spite of the usefulness of arguments in a decision…

Artificial Intelligence · Computer Science 2012-07-19 Leila Amgoud , Henri Prade

There is a generic way to add any new feature to a system. It involves 1) identifying the basic units which build up the system and 2) introducing the new feature to each of these basic units. In the case where the system is argumentation…

Artificial Intelligence · Computer Science 2015-03-19 D. M. Gabbay , O. Rodrigues

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

Results about the redundancy of circumscriptive and default theories are presented. In particular, the complexity of establishing whether a given theory is redundant is establihsed.

Logic in Computer Science · Computer Science 2021-04-12 Paolo Liberatore

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

Inferring from inconsistency and making decisions are two problems which have always been treated separately by researchers in Artificial Intelligence. Consequently, different models have been proposed for each category. Different…

Artificial Intelligence · Computer Science 2012-07-09 Leila Amgoud

Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more…

Artificial Intelligence · Computer Science 2021-05-12 Steven Schockaert , Yazmín Ibáñez-García , Víctor Gutiérrez-Basulto

We present a semantics for adding uncertainty to conditional logics for default reasoning and belief revision. We are able to treat conditional sentences as statements of conditional probability, and express rules for revision such as "If A…

Artificial Intelligence · Computer Science 2013-03-08 Craig Boutilier

We consider the immediate consequence of an arguable addition to the standard Deduction Theorems of first order theories.

General Mathematics · Mathematics 2007-05-23 Bhupinder Singh Anand

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem defaults were intended to avoid, or they generate peculiar side…

Artificial Intelligence · Computer Science 2013-04-10 Eric Neufeld , David L Poole

We present a new approach to dealing with default information based on the theory of belief functions. Our semantic structures, inspired by Adams' epsilon-semantics, are epsilon-belief assignments, where values committed to focal elements…

Artificial Intelligence · Computer Science 2013-02-21 Salem Benferhat , Alessandro Saffiotti , Philippe Smets