The article develops and justifies, on the basis of the epistemological argumentation theory, two central pieces of the theory of evaluative argumentation interpretation: 1. criteria for recognizing argument types and 2. rules for adding reasons to create ideal arguments. Ad 1: The criteria for identifying argument types are a selection of essential elements from the definitions of the respective argument types. Ad 2: After presenting the general principles for adding reasons (benevolence, authenticity, immanence, optimization), heuristics are proposed for finding missing (...) reasons, for deductive arguments, e.g., semantic tableaux are suggested. (shrink)

This paper presents a comprehensive study of argumentation frameworks with necessities (AFNs), a bipolar extension of Dung Abstract argumentation frameworks (AFs) where the support relation captures a positive interaction between arguments having the meaning of necessity: the acceptance of an argument may require the acceptance of other argument(s). The paper discusses new main acceptability semantics for AFNs and their characterization both by a direct approach and a labelling approach. It examines the relationship between AFNs and Dung AFs and shows the (...) gain provided by the former in terms of concision. Finally, the paper shows how to represent an AFN as a normal logic program (LP) and vice versa and in both cases establishes a one-to-one correspondence between extensions under the main acceptability semantics (except for semi-stable semantics where the correspondence is not completely full) of an AFN and particular cases of 3-valued stable models of normal LPs. (shrink)

Argumentation is a mechanism to support different forms of reasoning such as decision making and persuasion and always cast under the light of critical thinking. In the latest years, several comput...

Online debates typically possess a large number of argumentative comments. Most readers who would like to see which comments are winning arguments often only read a part of the debate. Many platforms that host such debates allow for the comments to be sorted, say from the earliest to latest. How can argumentation theory be used to evaluate the effectiveness of such policies of sorting comments, in terms of the actually winning arguments displayed to a reader who may not have read (...) the whole debate? We devise a pipeline that captures an online debate tree as a bipolar argumentation framework (BAF), which is sorted depending on the policy, giving a sequence of induced sub-BAFs representing how and how much of the debate has been read. Each sub-BAF has its own set of winning arguments, which can be quantitatively compared to the set of winning arguments of the whole BAF. We apply this pipeline to evaluate policies on Kialo debates, where it is shown that reading comments from most to least liked, on average, displays more winners than reading comments earliest first. Therefore, in Kialo, reading comments from most to least liked is on average more effective than reading from the earliest to the most recent. (shrink)

In spite of significant research efforts, argument technologies do not seem poised to scale up as much as most commentators would hope or even predict. In this paper, I discuss what obstacles bar the way to more widespread success of argument technologies and venture some suggestions on how to circumvent such difficulties: doing so will require a significant shift in how this research area is typically understood and practiced. I begin by exploring a much broader yet closely related question: To (...) what extent are people natively good at arguing? This issue has always been central to philosophical reflection and it has become even more urgent nowadays, with the explosion of persuasive technologies and unprecedented opportunities for large-scale social influence. The answer hinges on what aspect of argumentation is taken under consideration: evidence suggests that people are relatively bad at analyzing the structure of arguments, especially when these are presented out of context and in abstract terms; in contrast, data show that even laymen tend to excel in the interactive practice of argumentation, in particular when motivation is high and something significant is at stake. Unfortunately, current argument technologies are more closely tailored to the former type of activity than to the latter, which is the main reason behind their relative lack of success with the general public. Changing this state of affair will require a commitment to ecological argument technologies: that is, technologies designed to support real-time, engaging and meaningful argumentative interactions performed by laypeople in their ordinary life, instead of catering to the highly specific needs of a minority of niche users. (shrink)

This paper studies a fundamental mechanism by which conflicts between arguments are drawn from sentiments regarding acceptability of the arguments. Given sets of arguments, an inverse abstract argumentation problem seeks attack relations between arguments such that acceptability semantics interprets each argument in the sets of arguments as being acceptable in each of the attack relations. It is an inverse problem of the traditional problem we refer to as the forward abstract argumentation problem. Given an attack relation, the forward abstract argumentation (...) problem seeks sets of arguments such that acceptability semantics interprets each argument in the sets of arguments as being acceptable in the attack relation. We give a probabilistic model of argumentation-theoretic inference. It is a generative model formalising the process by which acceptability semantics interprets acceptability of arguments in a given attack relation. We show that it gives a broad view of solutions to the forward and inverse abstract argumentation problems. Specifically, solutions to the inverse and forward abstract argumentation problems are shown to be equivalent to a maximum likelihood estimate and maximum likelihood prediction, respectively, which are both available with the generative model. In addition, they are shown to be special cases of the posterior distribution and the evidence, respectively, which are both obtained by probabilistic inference on the generative model. We report an experiment result and application example of the generative model in the inverse problems. (shrink)