Jochen Heinsohn

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On the one hand, class ical terminological knowledge representation excludes the possi­ bility of handling uncertain concept descrip­ tions involving, e.g., "usually true" concept properties, generalized quantifiers, or excep­ tions. On the other hand, purely numer­ ical approaches for handling uncertainty in general are unable to consider terminologi­ cal(More)
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(More)
Read more and get great! That's what the book enPDFd uncertainty and vagueness in knowledge based systems numerical methods will give for every reader to read this book. This is an on-line book provided in this website. Even this book becomes a choice of someone to read, many in the world also loves it so much. As what we talk, when you read more every page(More)
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(More)
In this report we de ne a probabilistic extension for a basic terminological knowledge representation languages. Two kinds of probabilistic statements are introduced: statements about conditional probabilities between concepts and statements expressing uncertain knowledge about a speci c object. The usual model-theoretic semantics for terminological logics(More)