27,063 research outputs found
A QBF-based Formalization of Abstract Argumentation Semantics
Supported by the National Research Fund, Luxembourg (LAAMI project) and by the Engineering and Physical Sciences Research Council (EPSRC, UK), grant ref. EP/J012084/1 (SAsSY project).Peer reviewedPostprin
Preservation of Semantic Properties during the Aggregation of Abstract Argumentation Frameworks
An abstract argumentation framework can be used to model the argumentative
stance of an agent at a high level of abstraction, by indicating for every pair
of arguments that is being considered in a debate whether the first attacks the
second. When modelling a group of agents engaged in a debate, we may wish to
aggregate their individual argumentation frameworks to obtain a single such
framework that reflects the consensus of the group. Even when agents disagree
on many details, there may well be high-level agreement on important semantic
properties, such as the acceptability of a given argument. Using techniques
from social choice theory, we analyse under what circumstances such semantic
properties agreed upon by the individual agents can be preserved under
aggregation.Comment: In Proceedings TARK 2017, arXiv:1707.0825
Probabilistic Argumentation with Epistemic Extensions and Incomplete Information
Abstract argumentation offers an appealing way of representing and evaluating
arguments and counterarguments. This approach can be enhanced by a probability
assignment to each argument. There are various interpretations that can be
ascribed to this assignment. In this paper, we regard the assignment as
denoting the belief that an agent has that an argument is justifiable, i.e.,
that both the premises of the argument and the derivation of the claim of the
argument from its premises are valid. This leads to the notion of an epistemic
extension which is the subset of the arguments in the graph that are believed
to some degree (which we defined as the arguments that have a probability
assignment greater than 0.5). We consider various constraints on the
probability assignment. Some constraints correspond to standard notions of
extensions, such as grounded or stable extensions, and some constraints give us
new kinds of extensions
Extension-based Semantics of Abstract Dialectical Frameworks
One of the most prominent tools for abstract argumentation is the Dung's
framework, AF for short. It is accompanied by a variety of semantics including
grounded, complete, preferred and stable. Although powerful, AFs have their
shortcomings, which led to development of numerous enrichments. Among the most
general ones are the abstract dialectical frameworks, also known as the ADFs.
They make use of the so-called acceptance conditions to represent arbitrary
relations. This level of abstraction brings not only new challenges, but also
requires addressing existing problems in the field. One of the most
controversial issues, recognized not only in argumentation, concerns the
support cycles. In this paper we introduce a new method to ensure acyclicity of
the chosen arguments and present a family of extension-based semantics built on
it. We also continue our research on the semantics that permit cycles and fill
in the gaps from the previous works. Moreover, we provide ADF versions of the
properties known from the Dung setting. Finally, we also introduce a
classification of the developed sub-semantics and relate them to the existing
labeling-based approaches.Comment: To appear in the Proceedings of the 15th International Workshop on
Non-Monotonic Reasoning (NMR 2014
Extended RDF as a Semantic Foundation of Rule Markup Languages
Ontologies and automated reasoning are the building blocks of the Semantic
Web initiative. Derivation rules can be included in an ontology to define
derived concepts, based on base concepts. For example, rules allow to define
the extension of a class or property, based on a complex relation between the
extensions of the same or other classes and properties. On the other hand, the
inclusion of negative information both in the form of negation-as-failure and
explicit negative information is also needed to enable various forms of
reasoning. In this paper, we extend RDF graphs with weak and strong negation,
as well as derivation rules. The ERDF stable model semantics of the extended
framework (Extended RDF) is defined, extending RDF(S) semantics. A distinctive
feature of our theory, which is based on Partial Logic, is that both truth and
falsity extensions of properties and classes are considered, allowing for truth
value gaps. Our framework supports both closed-world and open-world reasoning
through the explicit representation of the particular closed-world assumptions
and the ERDF ontological categories of total properties and total classes
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