A hybrid approach for modeling uncertainty in terminological logics

This paper proposes a probabilistic extension of terminological logics. The extension maintains the original performance of drawing inferences in a hierarchy of terminological definitions. It enlarges the range of applicability to real world domains determined not only by definitional but also by uncertain knowledge. First, we introduce the propositionally complete terminological language ALC. On the basis of the language construct "probabilistic implication" it is shown how statistical information on concept dependencies can be represented. To guarantee (terminological and probabilistic) consistency, several requirements have to be met. Moreover, these requirements allow one to infer implicitly existent probabilistic relationships and their quantitative computation. By explicitly introducing restrictions for the ranges derived by instantiating the consistency requirements, exceptions can also be handled. In the categorical cases this corresponds to the overriding of properties in non monotonic inheritance networks. Consequently, our model applies to domains where both term descriptions and non-categorical relations between term extensions have to be represented

An empirical analysis of terminological representation systems

The family of terminological representation systems has its roots in the representation system KL-ONE. Since the development of this system more than a dozen similar representation systems have been developed by various research groups. These systems vary along a number of dimensions.In this paper, we present the results of an empirical analysis of six such systems. Surprisingly, the systems turned out to be quite diverse leading to problems when transporting knowledge bases from one system to another. Additionally, the runtime performance between different systems and knowledge bases varied more than we expected. Finally, our empirical runtime performance results give an idea of what runtime performance to expect from such representation systems. These findings complement previously reported analytical results about the computational complexity of reasoning in such systems

Terminological knowledge representation : a proposal for a terminological logic

This paper contains a proposal for a terminological logic. The formalisms for representing knowledge as well as the needed inferences are described

RCUBE A Platform for Intelligent Autonomous Systems

Abstract—An intelligent robot platform for autonomous systems with vision capabilities has been developed by the University of Applied Sciences Brandenburg in cooperation with SME’s. The system will be suitable as a research and education platform for universities, a basis for industrial applications and for private developers of robots. This paper presents an architecture overview and application details of the RCUBE system. RCUBE will be available in 2 modular versions: 1. a cost-effective platform for reactive robots and private developers 2. a performant platform for intelligent robots with image processing capabilities suitabl