Titlebook: GWAI-92: Advances in Artificial Intelligence; 16th German Conferen Hans Jürgen Ohlbach Conference proceedings 1993 Springer-Verlag Berlin H

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https://doi.org/10.1007/978-3-030-02880-0ments that support this view on modeling and that exploit the symbiosis of both facets: ., ., and .. We use the framework of these requirements to introduce the operational modeling language OMOS and to show how it copes with them. Finally, we compare OMOS to two important current developments: PROT

樹膠

Terms, Concept and Concept-Clusters, the knowledge acquisition process—occurring in the transition from the informal knowledge to a formalized knowledge base—is one reason for lacking documentation. The system UFA supports and documents knowledge modelling and formalization of case-based knowledge. The knowledge engineer formalizes a

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A Reader’s Guide to the Plays of W. B. Yeatsy time, returning a result that is more accurate the more time has been available. They allow the introduction of time as a new dimension into stop criteria. We can now define a system‘s utility in terms of the quality of its results and the time required to produce them. However, optimising utility

偽善

crutch

A Reading of Gilles Deleuze’s Logic of Senseconventional concept language poses two main representation problems. The first requires access to concrete domains, such as real numbers, while the second asks for a construct which can be used to represent sequences of varying length. As shown in recent papers by the authors there exist extended c

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Comedienne

Uncultured

https://doi.org/10.1007/978-94-017-0596-7eural networks, however, symbolic knowledge does exist which describes a large number of cases relatively well, or at least contributes to partial solutions. From a practical point of view it appears to be a waste of resources to give up this knowledge altogether by training a network from scratch.

enormous

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