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

A Comparative Study of Ranking-based Semantics for Abstract Argumentation

Argumentation is a process of evaluating and comparing a set of arguments. A way to compare them consists in using a ranking-based semantics which rank-order arguments from the most to the least acceptable ones. Recently, a number of such semantics have been proposed independently, often associated with some desirable properties. However, there is no comparative study which takes a broader perspective. This is what we propose in this work. We provide a general comparison of all these semantics with respect to the proposed properties. That allows to underline the differences of behavior between the existing semantics.Comment: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-2016), Feb 2016, Phoenix, United State

Legal Decisionmaking as a Responsible Intellectual Activity: A Continental Point of View

The legal decision in a concrete case is never completely given in advance in the statute. A theory of legal decisionmaking that sees the decider as someone who merely applies the law is inadequate to explain what goes on in the process of legal decisionmaking. The legal decision is a value synthesis assessing the normative starting point with regard to the factual starting point, and vice versa. This means that a legal decision can only be made when the normative state of constituent facts of the case has been formed on the basis of the statute, when from the life case the legally-relevant state of facts has been worked out, and when it has been established that the latter is an example of the normative state of constituent facts to which a certain legal consequence is linked. The theory of argumentation described in this essay examines the nature of the process of legal deciding as such, and offers to legal decisionmakers an appropriate methodology for understanding their own actions, and for filling up the ambiguous space between norm and facts with arguments that will make the decision legally persuasive, if not legally secure. But beyond a prescription for rhetorical effectiveness, the theory of argumentation shows that above all legal decisionmaking is a responsible intellectual activity

Some Supplementaries to The Counting Semantics for Abstract Argumentation

Dung's abstract argumentation framework consists of a set of interacting arguments and a series of semantics for evaluating them. Those semantics partition the powerset of the set of arguments into two classes: extensions and non-extensions. In order to reason with a specific semantics, one needs to take a credulous or skeptical approach, i.e. an argument is eventually accepted, if it is accepted in one or all extensions, respectively. In our previous work \cite{ref-pu2015counting}, we have proposed a novel semantics, called \emph{counting semantics}, which allows for a more fine-grained assessment to arguments by counting the number of their respective attackers and defenders based on argument graph and argument game. In this paper, we continue our previous work by presenting some supplementaries about how to choose the damaging factor for the counting semantics, and what relationships with some existing approaches, such as Dung's classical semantics, generic gradual valuations. Lastly, an axiomatic perspective on the ranking semantics induced by our counting semantics are presented.Comment: 8 pages, 3 figures, ICTAI 201

Graduality in Probabilistic Argumentation Frameworks

Gradual semantics are methods that evaluate overall strengths of individual arguments in graphs. In this paper, we investigate gradual semantics for extended frameworks in which probabilities are used to quantify the uncertainty about arguments and attacks belonging to the graph. We define the likelihoods of an argument’s possible strengths when facing uncertainty about the topology of the argumentation framework. We also define an approach to compare the strengths of arguments in this probabilistic setting. Finally, we propose a method to calculate the overall strength of each argument in the framework, and we evaluate this method against a set of principles

Semantics for Evidence-Based Argumentation

Postprin

Ranking-based semantics for argumentation frameworks

International audienceAn argumentation system consists of a set of interacting arguments and a semantics for evaluating them. This paper proposes a new family of semantics which rank-orders arguments from the most acceptable to the weakest one(s). The new semantics enjoy two other main features: i) an attack weakens its target but does not kill it, ii) the number of attackers has a great impact on the acceptability of an argument.We start by proposing a set of rational postulates that such semantics could satisfy, then construct various semantics that enjoy them