We present a new and compelling approach to the efficient solution of important computational problems that arise in the context of abstract argumentation. Our approach makes known algorithms defined for restricted fragments generally applicable, at a computational cost that scales with the distance from the fragment. Thus, in a certain sense, we gradually augment tractable fragments. Surprisingly, it turns out that some tractable fragments admit such an augmentation and that others do not. More specifically, we show that the problems of credulous and skeptical acceptance are fixed-parameter tractable when parameterized by the distance from the fragment of acyclic argumentation frameworks. Other tractable fragments such as the fragments of symmetrical and bipartite frameworks seem to prohibit an augmentation: the acceptance problems are already intractable for frameworks at distance 1 from the fragments. For our study we use a broad setting and consider several different semantics. For the algorithmic results we utilize recent advances in fixed-parameter tractability.

Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this paper, we propose a reasoning-based, interactive approach to support the revision of formalized knowledge. We state consistency criteria for revision states and introduce the notion of revision closure, based on which the revision of ontologies is partially automatized. Additionally, we propose a notion of axiom impact which is used to determine a beneficial order of axiom evaluation in order to further increase the effectiveness of ontology revision. Finally, we develop the notion of decision spaces, which are structures for calculating and updating the revision closure and axiom impact. The use of decision spaces saves on average 75% of the costly reasoning operations during a revision.

The ability to predict, or at least recognize, the state of the world that an action brings about, is a central feature of autonomous agents. We propose, herein, a formal framework within which we investigate whether this ability can be autonomously learned. The framework makes explicit certain premises that we contend are central in such a learning task: (i) slow sensors may prevent the sensing of an action's direct effects during learning; (ii) predictions need to be made reliably in future and novel situations. We initiate in this work a thorough investigation of the conditions under which learning is or is not feasible. Despite the very strong negative learnability results that we obtain, we also identify interesting special cases where learning is feasible and useful.

Despite the importance of propositional logic in artificial intelligence, the notion of language independence in the propositional setting (not to be confound with syntax independence) has not received much attention so far. In this paper, we define language independence for a propositional operator as robustness w.r.t.symbol translation. We provide a number of characterizations results for such translations. We motivate the need to focus on symbol translations of restricted types, and identify several families of interest. We identify the computational complexity of recognizing symbol translations from those families. Finally, as a case study, we investigate the robustness of belief revision/merging operators w.r.t. translations of different types. It turns out that rational belief revision/merging operators are not guaranteed to offer the most basic (yet non-trivial) form of language independence; operators based on the Hamming distance do not suffer from this drawback but are less robust than operators based on the drastic distance.

We study the existential closures of several propositional languages L considered recently as target languages for knowledge compilation (KC), namely the incomplete fragments KROM-C, HORN-C, K/H-C, renH-C, AFF, and the corresponding disjunction closures KROM-C[V], HORN-C[V], K/H-C[V], renH-C[V], and AFF[V]. We analyze the queries, transformations, expressiveness and succinctness of the resulting languages L[E] in order to locate them in the KC map. As a by-product, we also address several issues concerning disjunction closures that were left open so far. From our investigation, the language HORN-C[V, E] (where disjunctions and existential quantifications can be applied to Horn CNF formulae) appears as an interesting target language for the KC purpose, challenging the influential DNNF languages.

We study uniform interpolation and forgetting in the description logic ALC. Our main results are model-theoretic characterizations of uniform interpolants and their existence in terms of bisimulations, tight complexity bounds for deciding the existence of uniform interpolants, an approach to computing interpolants when they exist, and tight bounds on their size. We use a mix of model-theoretic and automata-theoretic methods that, as a by-product, also provides charachterizations of, and decision procedures for, conservative extensions.

Since the seminal work of Sampath et al. in 1996, despite the subsequent flourishing of techniques on diagnosis of discrete-event systems (DESs), the basic notions of fault and diagnosis have been remaining conceptually unchanged. Faults are defined at component level and diagnoses incorporate the occurrences of component faults within system evolutions: diagnosis is context-free. As this approach may be unsatisfactory for a complex DES, whose topology is organized in a hierarchy of abstractions, we propose to define different diagnosis rules for different subsystems in the hierarchy. Relevant fault patterns are specified as regular expressions on patterns of lower-level subsystems. Separation of concerns is achieved and the expressive power of diagnosis is enhanced: each subsystem has its proper set of diagnosis rules, which may or may not depend on the rules of other subsystems. Diagnosis is no longer anchored to components: it becomes context-sensitive. The approach yields seemingly contradictory but nonetheless possible scenarios: a subsystem can be normal despite the faulty behavior of a number of its components (positive paradox); also, it can be faulty despite the normal behavior of all its components (negative paradox).

Existential rules, i.e. Datalog extended with existential quantifiers in rule heads, are currently studied under a variety of names such as Datalog +/-, ∀∃-rules, and tuple-generating dependencies. The renewed interest in this formalism is fuelled by a wealth of recently discovered language fragments for which query answering is decidable. This paper extends and consolidates two of the main approaches in this field — acyclicity and guardedness — by providing (1) complexity-preserving generalisations of weakly acyclic and weakly (frontier-)guarded rules, and (2) a novel formalism of glut-(frontier-)guarded rules that subsumes both. This builds on an insight that acyclicity can be used to extend any existential rule language while retaining decidability. Besides decidability, combined query complexities are established in all cases.

We investigate (quantifier-free) spatial constraint languages with equality, contact and connectedness predicates as well as Boolean operations on regions, interpreted over low-dimensional Euclidean spaces. We show that the complexity of reasoning varies dramatically depending on the dimension of the space and on the type of regions considered. For example, the logic with the interior-connectedness predicate (and without contact) is undecidable over polygons or regular closed sets in the Euclidean plane, NP-complete over regular closed sets in three-dimensional Euclidean space, and ExpTime-complete over polyhedra in three-dimensional Euclidean space.

Existing belief merging operators take advantage of all the models from the bases, including those contradicting the integrity constraints. In this paper, we show that this is not suited to every merging scenario. We study the case when the bases are "rationalized" with respect to the integrity constraints during the merging process. We define in formal terms several independence conditions for merging operators and show how they interact with the standard IC postulates for belief merging. Especially, we give an independence-based axiomatic characterization of a distance-based operator.