Kaiserslautern - Fachbereich Informatik
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This paper describes a tableau-based higher-order theorem prover HOT and an application to natural language semantics. In this application, HOT is used to prove equivalences using world knowledge during higher-order unification (HOU). This extended form of HOU is used to compute the licensing conditions for corrections.
Simultaneous quantifier elimination in sequent calculus is an improvement over the well-known skolemization. It allows a lazy handling of instantiations as well as of the order of certain reductions. We prove the soundness of a sequent calculus which incorporates a rule for simultaneous quantifier elimination. The proof is performed by semantical arguments and provides some insights into the dependencies between various formulas in a sequent.
The notion of formal description techniques for timed systems (T-FDTs) has been introduced in [EDK98a] to provide a unifying framework for description techniques that are formal and that allow to describe the ongoing behavior of systems. In this paper we show that three well known temporal logics, MTL, MTL-R , and CTL*, can be embedded in this framework. Moreover, we provide evidence that a large number of dioeerent kinds of temporal logics can be considered as T-FDTs.
The paper addresses two problems of comprehensible proof presentation, the hierarchically structured presentation at the level of proof methods and different presentation styles of construction proofs. It provides solutions for these problems that can make use of proof plans generated by an automated proof planner.
Object-oriented case representations require approaches for similarity assessment that allow to compare two differently structured objects, in particular, objects belonging to different object classes. Currently, such similarity measures are developed more or less in an ad-hoc fashion. It is mostly unclear, how the structure of an object-oriented case model, e.g., the class hierarchy, influences similarity assessment. Intuitively, it is obvious that the class hierarchy contains knowledge about the similarity of the objects. However, how this knowledge relates to the knowledge that could be represented in similarity measures is not obvious at all. This paper analyzes several situations in which class hierarchies are used in different ways for case modeling and proposes a systematic way of specifying similarity measures for comparing arbitrary objects from the hierarchy. The proposed similarity measures have a clear semantics and are computationally inexpensive to compute at run-time.
Contrary to symbolic learning approaches, that represent a learned concept explicitly, case-based approaches describe concepts implicitly by a pair (CB; sim), i.e. by a measure of similarity sim and a set CB of cases. This poses the question if there are any differences concerning the learning power of the two approaches. In this article we will study the relationship between the case base, the measure of similarity, and the target concept of the learning process. To do so, we transform a simple symbolic learning algorithm (the version space algorithm) into an equivalent case-based variant. The achieved results strengthen the hypothesis of the equivalence of the learning power of symbolic and casebased methods and show the interdependency between the measure used by a case-based algorithm and the target concept.
We present a parallel path planning method that is able to automatically handle multiple goal configurations as input. There are two basic approaches, goal switching and bi-directional search, which are combined in the end. Goal switching dynamically selects a fa-vourite goal depending on some distance function. The bi-directional search supports the backward search direction from the goal to the start configuration, which is probably faster. The multi-directional search with goal switching combines the advantages of goal switching and bi-directional search. Altogether, the planning system is enabled to select one of the pref-erable goal configuration by itself. All concepts are experimentally validated for a set of benchmark problems consisting of an industrial robot arm with six degrees of freedom in a 3D environment.
Es wird die Aufgabe der vollständigen räumlichen Abdeckung von Regionen in durch mobile Roboter betrachtet. Da-bei können die Regionen in vollständig, teilweise oder nicht bekannten Umgebungen liegen. Zur Lösung wird ein Verfahren aus der Computer-grafik zum Füllen von Bildregionen zugrunde gelegt. Das Verfahren hat eine lokale Sichtweise und läßt somit den Einsatz von Sensordaten und das Auftreten von unvorhergesehenen Hindernissen zu. Die Regionen können durch Karten off-line vorgegeben sein oder durch Sensordaten on-line aufgebaut werden. Dennoch ist eine vollständige und genau einma-lige Flächenbearbeitung garantiert. Dies wird an Beispielen in einer graphischen Visualisierung der Realzeit-Steuerung des Roboters validiert.