Probabilistic argumentation and neuro-argumentative systems offer new computational perspectives for the theory and applications of argumentation, but their principled construction involve two entangled problems. On the one hand, probabilistic argumentation aims at combining the quantitative uncertainty addressed by probability theory with the qualitative uncertainty of argumentation, but proba...

This article approaches the relationship of normative argumentation studies and descriptive persuasion effects research by pointing to several empirical findings that raise questions or puzzles about normatively-proper argumentative conduct. These findings indicate some complications in the analysis of normatively desirable argumentative conduct – including some ways in which practical persuasi...

Arguing that a varying level of formality needs to be offered in systems supporting argumentative collaboration, this article proposes an incremental formalization approach that has been adopted in the development of CoPe_it!, a Web-based tool that complies with collaborative principles and practices, and provides members of communities engaged in argumentative discussions and decision making p...

academic writing ability is an important goal that learners of english as a second language (esl) or english as a foreign language (efl) try to attain. while esl students’ academic writings have been widely explored, owing to few studies investigating appraisal resources in efl students’ argumentative writing, the gap still exists about efl students’ academic writing. this study aimed to see ho...

Argumentative interactions in online asynchronous communication are seldom studied by using a qualitative approach as Grounded Theory Methods. The purpose of this paper is about a theory of argumentation based on analysis of teacher-student and learner-learner dialogues. By examining linguistic features of the threads related to the forum of two different academic courses, we consider the struc...

While neural networks have been successfully used in a number of machine learning applications, logical languages have been the standard for the representation of legal and argumentative reasoning [6]. In this paper, we present a new hybrid model of computation that allows for the deduction and learning of argumentative reasoning. We do so by using Neural-Symbolic Learning Systems to translate ...