Gaming argumentation framework (GAF): Pfizer or AstraZeneca Vaccine of The COVID-19 as a case study

Dung’s argumentation frameworks (AF) were introduced in the last century it works with the justification of the argument. This framework analyzes attacks of arguments, it works away on the characteristics of arguments structures and words was used in the attack between each other, etc. These properties make this model attractive as it decreases most of the complexities included when applying the argumentation system. This system can be applied to different states such as to evaluate the arguments or with the supported argument to be defense and attacked arguments. In addition, the group of experts may be making argumentation about some cases. In the latter scenario, agents with potentially dissimilar arguments and/or opinions are used to evaluate the arguments, allowing for the consideration of several sets of arguments and attack relations. This framework is extended to propose a new system called gaming argumentation framework (GAF). It helps to make a decision about the current problem by making claims and attack determination to the arguments, then putting the result of these claims and attack determination to the game theory with two players to achieve the final results that help the decision-maker to decide about the current problem. Finally, compare this framework with other frameworks, and provide an example to explain how the proposed framework performs its intended purpose, where decision making is very important in the medical field therefore this paper taking the confusion on the COVID-19 vaccines as a case study to solve Pfizer or AstraZeneca problem and make the decision about this case

Towards a Computational Analysis of Probabilistic Argumentation Frameworks

In this paper we analyze probabilistic argumentation frameworks (PAFs), defined as an extension of Dung abstract argumentation frameworks in which each argument n is asserted with a probability p(n). The debate around PAFs has so far centered on their theoretical definition and basic properties. This work contributes to their computational analysis by proposing a first recursive algorithm to compute the probability of acceptance of each argument under grounded and preferred semantics, and by studying the behavior of PAFs with respect to reinstatement, cycles and changes in argument structure. The computational tools proposed may provide strategic information for agents selecting the next step in an open argumentation process and they represent a contribution in the debate about gradualism in abstract argumentation

Bipolarity in argumentation graphs: Towards a better understanding

Edited by Benferhat Salem, Philippe LerayInternational audienceDifferent abstract argumentation frameworks have been used for various applications within multi-agents systems. Among them, bipolar frameworks make use of both attack and support relations between arguments. However, there is no single interpretation of the support, and the handling of bipolarity cannot avoid a deeper analysis of the notion of support.In this paper we consider three recent proposals for specializing the support relation in abstract argumentation: the deductive support, the necessary support and the evidential support. These proposals have been developed independently within different frameworks. We restate these proposals in a common setting, which enables us to undertake a comparative study of the modellings obtained for the three variants of the support. We highlight relationships and differences between these variants, namely a kind of duality between the deductive and the necessary interpretations of the support

Etude du changement en argumentation : de la théorie à la pratique

L'argumentation, au sens de l'intelligence artificielle, est un formalisme permettant de raisonner à partir d'informations incomplètes et/ou contradictoires ainsi que de modéliser un échange d'arguments entre plusieurs agents. Un système d'argumentation consiste généralement en un ensemble d'arguments interagissant les uns avec les autres, et duquel il est possible d'extraire un ou plusieurs points de vue cohérents. Dans cette thèse, nous nous plaçons dans le cadre de l'argumentation abstraite dans lequel les arguments sont manipulés en tant qu'entités abstraites dont le sens nous est inconnu et dans lequel les interactions représentent des conflits. Ceci nous permet de nous concentrer sur le point particulier de la dynamique dans les systèmes d'argumentation abstraits, c'est-à-dire les changements pouvant impacter ces systèmes, notamment dans le cadre d'un dialogue. Nous commençons par justifier l'intérêt d'un tel cadre formel puis nous nous intéressons au comment et au pourquoi du changement en argumentation abstraite. Le comment est approché en établissant une liste des modifications que peut subir un système d'argumentation et en étudiant sous quelles conditions elles peuvent survenir. Le pourquoi est abordé par l'introduction de la notion de but motivant un changement et le choix du meilleur changement à faire pour satisfaire un but en prenant en considération des contraintes portant sur l'agent à convaincre. Enfin, nous concrétisons notre étude en proposant un outil logiciel implémentant les notions introduites et nous étudions ses performances.Argumentation, in the field of artificial intelligence, is a formalism allowing to reason with incomplete and/or contradictory information as well as to model an exchange of arguments between several agents. An argumentation system usually consists of a set of arguments interacting with each other, and from which it is possible to extract one or several consistent points of view. In this thesis, we are mainly concerned with the abstract argumentation in which arguments are handled as abstract entities whose meaning is unknown and in which the interactions represent conflicts. This allows us to focus on the particular point of the dynamics in abstract argumentation systems, that is to say the changes that could impact these systems, particularly in the context of a dialogue. We start with justifying the interest of such a formal framework, then we study the how and the why of change in abstract argumentation. The how is tackled by establishing a list of changes that an argumentation system can undergo and by studying the conditions under which they may occur. The why is addressed by introducing the notion of goal motivating a change and by choosing the best change to make in order to satisfy a goal, taking into account constraints on the agent to convince. Finally, we make our study concrete by proposing a tool that implements the concepts introduced and we study its performance

Inconsistency tolerance in weighted argument systems

We introduce and investigate a natural extension of Dung’s wellknown model of argument systems in which attacks are associated with a weight, indicating the relative strength of the attack. A key concept in our framework is the notion of an inconsistency budget, which characterises how much inconsistency we are prepared to tolerate: given an inconsistency budget β, we would be prepared to disregard attacks up to a total cost of β. The key advantage of this approach is that it permits a much �ner grained level of analysis of argument systems than unweighted systems, and gives useful solutions when conventional (unweighted) argument systems have none. We begin by reviewing Dung’s abstract argument systems, and present the model of weighted argument systems. We then investigate solutions to weighted argument systems and the associated complexity of computing these solutions, focussing in particular on weighted variations of grounded extensions