Fuzzy description logics (DLs) have been investigated for over two decades, due to their capacity to formalize and reason with imprecise concepts. Very recently, it has been shown that for several fuzzy DLs, reasoning becomes undecidable. Although the proofs of these results differ in the details of each specific logic considered, they are all based on the same basic idea. In this paper, we formalize this idea and provide sufficient conditions for proving undecidability of a fuzzy DL. We demonstrate the effectiveness of our approach by strengthening all previously-known undecidability results and providing new ones. In particular, we show that undecidability may arise even if only crisp axioms are considered.

While query answering in the presence of description logic (DL) ontologies is a well-studied problem, questions of static analysis such as query containment and query optimization have received less attention. In this paper, we study a rather general version of query containment that, unlike the classical version, cannot be reduced to query answering. First, we allow a restriction to be placed on the vocabulary used in the instance data, which can result in shorter equivalent queries; and second, we allow each query its own ontology rather than assuming a single ontology for both queries, which is crucial in applications to versioning and modularity. We also study global minimization of queries in the presence of DL ontologies, which is more subtle than for classical databases as minimal queries need not be isomorphic.

This paper presents an axiomatic framework for influence diagram computation, which allows reasoning with partially ordered values of utility. We show how an algorithm based on sequential variable elimination can be used to compute the set of maximal values of expected utility (up to an equivalence relation). Formalisms subsumed by the framework include decision making under uncertainty based on multi-objective utility, or on interval-valued utilities, as well as a more qualitative decision theory based on order-of-magnitude probabilities and utilities.

We deal with the problem of how to extend a preference relation over a set X of "objects" to the set of all subsets of X. This problem has been carried out in the tradition of the literature on extending an order on a set to its power set with the objective to analyze the axiomatic structure of families of rankings over subsets. In particular, most of these approaches make use of axioms aimed to prevent any kind of interaction among the objects in X . In this paper, we apply coalitional games to study the problem of extending preferences over a finite set X to its power set 2 X . A coalitional game can be seen as a numerical representation of a preference extension on 2 X . . We focus on a particular class of extensions on 2 X . such that the ranking induced by the Shapley value of each coalitional game representing an extension in this class, coincides with the original preference on X . Some properties of Shapley extensions are discussed, with the objective to justify and contextualize the application of Shapley extensions to the problem of ranking sets of possibly interacting objects.We deal with the problem of how to extend a preference relation over a set X of "objects" to the set of all subsets of X . This problem has been carried out in the tradition of the literature on extending an order on a set to its power set with the objective to analyze the axiomatic structure of families of rankings over subsets. In particular, most of these approaches make use of axioms aimed to prevent any kind of interaction among the objects in X . In this paper, we apply coalitional games to study the problem of extending preferences over a finite set X to its power set 2 X . . A coalitional game can be seen as a numerical representation of a preference extension on 2 X . . We focus on a particular class of extensions on 2 X. such that the ranking induced by the Shapley value of each coalitional game representing an extension in this class, coincides with the original preference on X . Some properties of Shapley extensions are discussed, with the objective to justify and contextualize the application of Shapley extensions to the problem of ranking sets of possibly interacting objects.

We introduce the framework of qualitative optimization problems (or, simply, optimization problems) to represent preference theories. The formalism uses separate modules to describe the space of outcomes to be compared (the generator) and the preferences on outcomes (the selector). We consider two types of optimization problems. They differ in the way the generator, which we model by a propositional theory, is interpreted: by the standard propositional logic semantics, and by the equilibrium-model (answer-set) semantics. Under the latter interpretation of generators, optimization problems directly generalize answer-set optimization programs proposed previously. We study strong equivalence of optimization problems, which guarantees their interchangeability within any larger context. We characterize several versions of strong equivalence obtained by restricting the class of optimization problems that can be used as extensions and establish the complexity of associated reasoning tasks. Understanding strong equivalence is essential for modular representation of optimization problems and rewriting techniques to simplify them without changing their inherent properties.

Following the recent trend of adapting the AGM (Alchourron and Makinson 1985) framework to propositional Horn logic, Delgrande and Peppas (Delgrande and Peppas 2011) give a model theoretic account for revision in the Horn logic set- ting. The current paper complements their work by studying the model theoretic approach for contraction. A model based Horn contraction is constructed and shown to give a model theoretic account to the transitively relational partial meet Horn contraction studied in (Zhuang and Pagnucco 2011). Significantly however, in contrast to (Delgrande and Pep- pas 2011), our model-based characterisation of Horn contrac- tion does not require the property of Horn compliance and totality over preorders. The model based contraction, upon proper restriction, also gives a model theoretic account for the epistemic entrenchment based Horn contraction studied in (Zhuang and Pagnucco 2010a).

Existing methods for dealing with knowledge updates differ greatly depending on the underlying knowledge representation formalism. When Classical Logic is used, update operators are typically based on manipulating the knowledge base on the model-theoretic level. On the opposite side of the spectrum stand the semantics for updating Answer-Set Programs where most approaches need to rely on rule syntax. Yet, a unifying perspective that could embrace all these approaches is of great importance as it enables a deeper understanding of all involved methods and principles and creates room for their cross-fertilisation, ripening and further development. This paper bridges these seemingly irreconcilable approaches to updates. It introduces a novel monotonic characterisation of rules, dubbed \emph{\RE-models}, and shows it to be a more suitable semantic foundation for rule updates than \SE-models. A generic framework for defining semantic rule update operators is then proposed. It is based on the idea of viewing a program as the \emph{set of sets of \RE-models} of its rules; updates are performed by introducing additional interpretations to the sets of \RE-models of rules in the original program. It is shown that particular instances of the framework are closely related to both belief update principles and traditional approaches to rule updates and enjoy a range of plausible syntactic as well as semantic properties.

An agent will generally have incomplete and possibly inaccurate knowledge about its environment. In addition, such an agent may receive erroneous information, perhaps in being misinformed about the truth of some formula. In this paper we present a general approach to reasoning about action and belief change in such a setting. An agent may carry out actions, but in some cases may inadvertently execute the wrong one (for example, pushing an unintended button). As well, an agent may sense whether a condition holds, and may revise its beliefs after being told that a formula is true. Our approach is based on an epistemic extension to basic action theories expressed in the situation calculus, augmented by a plausibility relation over situations. This plausibility relation can be thought of as characterising the agent's overall belief state; as such it keeps track of not just the formulas that the agent believes to hold, but also the plausibility of formulas that it does not believe to hold. The agent's belief state is updated by suitably modifying the plausibility relation following the execution of an action. We show that our account generalises previous approaches, and fully handles belief revision, sensing, and erroneous actions.

The dynamic nature of ontology development has motivated the formal study of ontology evolution problems. This paper presents a logical framework that enables fine-grained investigation of evolution problems at a deductive level. In our framework, the optimal evolutions of an ontology O are those ontologies O′ that maximally preserve both the structure of O and its entailments in a given preservation language. We show that our framework is compatible with the postulates of Belief Revision, and we investigate the existence of optimal evolutions in various settings. In particular, we present first results on TBox-level revision and contraction in the EL and FL0 families of Description Logics.

Belief revision has been extensively studied in the framework of propositional logic, but just recently revision within fragments of propositional logic has gained attention. Hereby it is not only the belief set and the revision formula which are given within a certain language fragment, but also the result of the revision has to be located in the same fragment. So far, research in this direction has been mainly devoted to the Horn fragment of classical logic. In this work, we present a general approach to define new revision operators derived from known operators (as for instance, Satoh's and Dalal's revision operators), such that the result of the revision remains in the fragment under consideration. Our approach is not limited to the Horn case but applicable to any fragment of propositional logic where the models of the formulas are closed under a Boolean function. Thus we are able to uniformly treat cases as dual-Horn, Krom and affine formulas, as well.