3 research outputs found
Capturing Bipolar Argumentation in Non-flat Assumption-Based Argumentation
Bipolar Argumentation Frameworks (BAFs) encompass both attacks and supports among arguments. We study different semantic interpretations of support in BAFs, particularly necessary and deductive support, as well as argument coalitions and a recent proposal by Gabbay. We analyse the relationship of these different notions of support in BAFs with the semantics of a well established structured argumentation formalism, Assumption-Based Argumentation (ABA), which predates BAFs. We propose natural mappings from BAFs into a restricted class of (non-flat) ABA frameworks, which we call bipolar, and prove that the admissible and preferred semantics of these ABA frameworks correspond to the admissible and preferred semantics of the various approaches to BAFs. Motivated by the definition of stable semantics for BAFs, we introduce a novel set-stable semantics for ABA frameworks, and prove that it corresponds to the stable semantics of the various approaches to BAFs. Finally, as a by-product of modelling various approaches to BAFs in bipolar ABA, we identify precise semantic relationships amongst all approaches we consider
Theme Aspect Argumentation Model for Handling Fallacies
From daily discussions to marketing ads to political statements, information
manipulation is rife. It is increasingly more important that we have the right
set of tools to defend ourselves from manipulative rhetoric, or fallacies.
Suitable techniques to automatically identify fallacies are being investigated
in natural language processing research. However, a fallacy in one context may
not be a fallacy in another context, so there is also a need to explain how and
why it has come to be judged a fallacy. For the explainable fallacy
identification, we present a novel approach to characterising fallacies through
formal constraints, as a viable alternative to more traditional fallacy
classifications by informal criteria. To achieve this objective, we introduce a
novel context-aware argumentation model, the theme aspect argumentation model,
which can do both: the modelling of a given argumentation as it is expressed
(rhetorical modelling); and a deeper semantic analysis of the rhetorical
argumentation model. By identifying fallacies with formal constraints, it
becomes possible to tell whether a fallacy lurks in the modelled rhetoric with
a formal rigour. We present core formal constraints for the theme aspect
argumentation model and then more formal constraints that improve its fallacy
identification capability. We show and prove the consequences of these formal
constraints. We then analyse the computational complexities of deciding the
satisfiability of the constraints