Complexity Results and Practical Algorithms for Logics in Knowledge Representation

Description Logics (DLs) are used in knowledge-based systems to represent and reason about terminological knowledge of the application domain in a semantically well-defined manner. In this thesis, we establish a number of novel complexity results and give practical algorithms for expressive DLs that provide different forms of counting quantifiers. We show that, in many cases, adding local counting in the form of qualifying number restrictions to DLs does not increase the complexity of the inference problems, even if binary coding of numbers in the input is assumed. On the other hand, we show that adding different forms of global counting restrictions to a logic may increase the complexity of the inference problems dramatically. We provide exact complexity results and a practical, tableau based algorithm for the DL SHIQ, which forms the basis of the highly optimized DL system iFaCT. Finally, we describe a tableau algorithm for the clique guarded fragment (CGF), which we hope will serve as the basis for an efficient implementation of a CGF reasoner.Comment: Ph.D. Thesi

Adding Causal Relationships to DL-based Action Formalisms

In the reasoning about actions community, causal relationships have been proposed as a possible approach for solving the ramification problem, i. e., the problem of how to deal with indirect effects of actions. In this paper, we show that causal relationships can be added to action formalisms based on Description Logics without destroying the decidability of the consistency and the projection problem

Temporalised Description Logics for Monitoring Partially Observable Events

Inevitably, it becomes more and more important to verify that the systems surrounding us have certain properties. This is indeed unavoidable for safety-critical systems such as power plants and intensive-care units. We refer to the term system in a broad sense: it may be man-made (e.g. a computer system) or natural (e.g. a patient in an intensive-care unit). Whereas in Model Checking it is assumed that one has complete knowledge about the functioning of the system, we consider an open-world scenario and assume that we can only observe the behaviour of the actual running system by sensors. Such an abstract sensor could sense e.g. the blood pressure of a patient or the air traffic observed by radar. Then the observed data are preprocessed appropriately and stored in a fact base. Based on the data available in the fact base, situation-awareness tools are supposed to help the user to detect certain situations that require intervention by an expert. Such situations could be that the heart-rate of a patient is rather high while the blood pressure is low, or that a collision of two aeroplanes is about to happen. Moreover, the information in the fact base can be used by monitors to verify that the system has certain properties. It is not realistic, however, to assume that the sensors always yield a complete description of the current state of the observed system. Thus, it makes sense to assume that information that is not present in the fact base is unknown rather than false. Moreover, very often one has some knowledge about the functioning of the system. This background knowledge can be used to draw conclusions about the possible future behaviour of the system. Employing description logics (DLs) is one way to deal with these requirements. In this thesis, we tackle the sketched problem in three different contexts: (i) runtime verification using a temporalised DL, (ii) temporalised query entailment, and (iii) verification in DL-based action formalisms

Complexity of the Guarded Two-Variable Fragment with Counting Quantifiers

We show that the finite satisfiability problem for the guarded two-variable fragment with counting quantifiers is in EXPTIME. The method employed also yields a simple proof of a result recently obtained by Y. Kazakov, that the satisfiability problem for the guarded two-variable fragment with counting quantifiers is in EXPTIME.Comment: 20 pages, 3 figure

OCL-Lite: a decidable (yet expressive) fragment of OCL

UML has become a de facto standard in conceptual modeling. Class diagrams in UML allow one to model the data in the domain of interest by specifying a set of graphical constraints. However, in most cases one needs to provide the class diagram with additional semantics to completely specify the domain, and this is where OCL comes into play. While reasoning over class diagrams is decidable and has been investigated intensively, it is well known that checking the correctness of OCL constraints is undecidable. Thus, we introduce OCL-Lite, a fragment of the full OCL language and prove that reasoning over UML class diagrams with OCL-Lite constraints is in ExpTime by an encoding in the description logic ALCI. As a side result, DL techniques and tools can be used to reason on UML class diagrams annotated with arbitrary OCL-Lite constraints.Peer ReviewedPostprint (published version