"Minimal defence": a refinement of the preferred semantics for argumentation frameworks

Dung's abstract framework for argumentation enables a study of the interactions between arguments based solely on an ``attack'' binary relation on the set of arguments. Various ways to solve conflicts between contradictory pieces of information have been proposed in the context of argumentation, nonmonotonic reasoning or logic programming, and can be captured by appropriate semantics within Dung's framework. A common feature of these semantics is that one can always maximize in some sense the set of acceptable arguments. We propose in this paper to extend Dung's framework in order to allow for the representation of what we call ``restricted'' arguments: these arguments should only be used if absolutely necessary, that is, in order to support other arguments that would otherwise be defeated. We modify Dung's preferred semantics accordingly: a set of arguments becomes acceptable only if it contains a minimum of restricted arguments, for a maximum of unrestricted arguments.Comment: 8 pages, 3 figure

Graduality in Argumentation

Argumentation is based on the exchange and valuation of interacting arguments, followed by the selection of the most acceptable of them (for example, in order to take a decision, to make a choice). Starting from the framework proposed by Dung in 1995, our purpose is to introduce 'graduality' in the selection of the best arguments, i.e., to be able to partition the set of the arguments in more than the two usual subsets of 'selected' and 'non-selected' arguments in order to represent different levels of selection. Our basic idea is that an argument is all the more acceptable if it can be preferred to its attackers. First, we discuss general principles underlying a 'gradual' valuation of arguments based on their interactions. Following these principles, we define several valuation models for an abstract argumentation system. Then, we introduce 'graduality' in the concept of acceptability of arguments. We propose new acceptability classes and a refinement of existing classes taking advantage of an available 'gradual' valuation

Inference from controversial arguments

International audienceWe present new careful semantics within Dung's theory of argumentation. Under such careful semantics, two arguments cannot belong to the same extension whenever one of them indirectly attacks a third argument while the other one indirectly defends the third.We argue that our semantics lead to a better handling of controversial arguments than Dung's ones in some settings. We compare the careful inference relations induced by our semantics w.r.t. cautiousness; we also compare them with the inference relations induced by Dung's semantic

Computing Argument Preferences and Explanations in Abstract Argumentation

Financial support from The UK Engineering and Physical Sciences Research Council (EPSRC) for the grant (EP/P011829/1), Supporting Security Policy with Effective Digital Intervention (SSPEDI) is gratefully acknowledged.Postprin

Towards Computational Persuasion via Natural Language Argumentation Dialogues

Computational persuasion aims to capture the human ability to persuade through argumentation for applications such as behaviour change in healthcare (e.g. persuading people to take more exercise or eat more healthily). In this paper, we review research in computational persuasion that incorporates domain modelling (capturing arguments and counterarguments that can appear in a persuasion dialogues), user modelling (capturing the beliefs and concerns of the persuadee), and dialogue strategies (choosing the best moves for the persuader to maximize the chances that the persuadee is persuaded). We discuss evaluation of prototype systems that get the user’s counterarguments by allowing them to select them from a menu. Then we consider how this work might be enhanced by incorporating a natural language interface in the form of an argumentative chatbot

Enhancing Goal-based Requirements Consistency: an Argumentation-based Approach

International audienceRequirements engineering research has for long recognized the leading role of goals as requirement artifacts during the requirements engineering specification processes. Given the large number of artifacts created during the requirements specification and the continuous evolution of these artifacts, reasoning about them remains a challenging task. Moreover, the rising complexity of the target domain under consideration during the requirements engineering process as well as the growth of geographically distributed projects explain why the number of collected requirements as well as their complexity also increase. In this context, providing support to stakeholders in achieving a common understanding of a set of goal-based requirements, in consolidating them and keeping them consistent over time is another challenging task. In this paper, we propose an approach to detect consistent sets of goal-based requirements and maintain their consistency over time. Our approach relies on argumentation theory which allows to detect the conflicts among elements called arguments. In particular, we rely on meta-argumentation, which instantiates abstract argumentation frameworks, where requirements are represented as arguments and the standard Dung-like argumentation framework is extended with additional relations between goal-based requirements