While agent-based modelling languages naturally implement concurrency, the currently available languages for argumentation do not allow to explicitly model this type of interaction. In this paper we introduce a concurrent language for handling agents arguing and communicating using a shared argumentation space. We also show how to perform high-level operations like persuasion and negotiation through basic belief revision constructs, and present a working implementation of the language and the associated web interface.

We present an analysis of ethical argumentation and rhetorical elements in an article on the debate about growing genetically modified food (GMF), an issue of current interest in environmental ethics. Ethical argumentation is argumentation that a certain action is permissible, forbidden, or obligatory in terms of ethical intuitions, principles, or theories. Based on analysis of argumentation in the article, we propose several argumentation schemes for descriptive modeling of utilitarian arguments as an alternative to using more general schemes such as practical (...) reasoning and argument from consequences. We also show how the article promoted its pro-GMF stance using rhetorical elements such as quotation, argument from expert opinion, and ad hominem attacks. Pedagogical and computational implications of the analysis of argumentation and rhetoric are discussed. (shrink)

Explainable artificial intelligence has become a vitally important research field aiming, among other tasks, to justify predictions made by intelligent classifiers automatically learned from data. Importantly, efficiency of automated explanations may be undermined if the end user does not have sufficient domain knowledge or lacks information about the data used for training. To address the issue of effective explanation communication, we propose a novel information-seeking explanatory dialogue game following the most recent requirements to automatically generated explanations. Further, we generalise our (...) dialogue model in form of an explanatory dialogue grammar which makes it applicable to interpretable rule-based classifiers that are enhanced with the capability to provide textual explanations. Finally, we carry out an exploratory user study to validate the corresponding dialogue protocol and analyse the experimental results using insights from process mining and argument analytics. A high number of requests for alternative explanations testifies the need for ensuring diversity in the context of automated explanations. (shrink)