Belief Revision in Structured Probabilistic Argumentation

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates -- based on well-known ones developed for classical knowledge bases -- that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates

On the Acceptability of Incompatible Arguments

Abstract. In this paper we study the acceptability of incompatible arguments within Dung’s abstract argumentation framework. As an example we introduce an instance of Dung’s framework where arguments are represented by propositional formulas and an argument attacks another one when the conjunction of their representations is inconsistent, which we characterize as a kind of symmetric attack. Since symmetric attack is known to have the drawback to collapse the various argumentation semantics, we consider also two variations. First, we consider propositional arguments distinguishing support and conclusion. Second, we introduce a preference ordering over the arguments and we define the attack relation in terms of a symmetric incompatibility relation and the preference relation. We show how to characterize preference-based argumentation using a kind of acyclic attack relation.

Tracing the Rationale Behind UML Model Change Through Argumentation

Abstract. Neglecting traceability—i.e., the ability to describe and follow the life of a requirement—is known to entail misunderstanding and miscommunication, leading to the engineering of poor quality systems. Following the simple principles that (a) changes to UML model instances ought be justified to the stakeholders, (b) justification should proceed in a structured manner to ensure rigor in discussions, critique, and revisions of model instances, and (c) the concept of argument instantiated in a justification process ought to be well defined and understood, the present paper introduces the UML Traceability through Argumentation Method (UML-TAM) to enable the traceability of design rationale in UML while allowing the appropriateness of model changes to be checked by analysis of the structure of the arguments provided to justify such changes.