Emil Weydert

Issues in uncertainty in AI: editorial

In database systems one often has to deal with constraints in order to compel the semantics of the stored data or to express some querying criteria. This is especially the case for multimedia database systems where information of different media types, as e.g. sound, video, images and texts, needs to be managed. A problem with the modelling of (the uncertainty about) the degree of satisfaction of a constraint, is the handling of missing information. In this paper, it is shown how extended possibilistic truth values can be employed to cope with this problem. The notion of an extended possibilistic truth value has been obtained from the assumption that the truth value, which expresses the degree of satisfaction of a constraint, can be undefined. This is for example the case if the constraint cannot be evaluated due to the non-applicability of (some of) its elements. An illustrative database definition and database querying example is presented and discussed.

System JLZ: rational default reasoning by minimal ranking constructions

We present a powerful quasi-probabilistic default formalism for graded defaults based on a well-motivated canonical ranking construction procedure, System JLZ. It implements the minimal construction paradigm and verifies the major inference principles and inheritance desiderata, including rational monotony for propositions and structured cumulativity for default conditionals. With help from a structured ranking semantics for defaults, it also avoids some drawbacks of semi-qualitative entropy maximization and other competing accounts.

On the Acceptability of Incompatible Arguments

In this paper we study the acceptability of incompatible arguments within Dungs abstract argumentation framework. As an example we introduce an instance of Dungs 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.

Projective default epistemology

We show how to extract iterated revision strategies for complex evidence, e.g. epistemic conditionals, from reasonable default inference notions. This approach allows a more extensive cross-fertilization between default reasoning and belief revision. To illustrate it, we use powerful default formalisms exploiting canonical ranking constructions, like system JZ, for specifying new ranking-based revision mechanisms. They extend Spohns ranking revision to sets of conditionals and satisfy basic rationality principles.

Conditional Ranking Revision - Iterated revision with sets of conditionals

In the context of a general framework for belief dynamics which interprets revision as doxastic constraint satisfaction, we discuss a proposal for revising quasi-probabilistic belief measures with finite sets of graded conditionals. The belief states are ranking measures with divisible values (generalizing Spohn’s epistemology), and the conditionals are interpreted as ranking constraints. The approach is inspired by the minimal information paradigm and based on the principle-guided canonical construction of a ranking model of the input conditionals. This is achieved by extending techniques known from conditional default reasoning. We give an overview of how it handles different principles for conditional and parallel revision and compare it with similar accounts.

On the plausibility of abstract arguments

We propose and investigate a plausibility-based extension semantics for abstract argumentation frameworks based on their generic instantiation by default knowledge bases and the ranking construction paradigm for default reasoning.