Abstract
We introduce a model and a system architecture for second-order reasoning about statements expressed in a (first-order) terminological representation language. This meta-reasoning approach is based on the reification of first-order propositions and the mediation between second- and first-order expressions via translation rules operating on multiple contexts. An application to a concept learning task in a text understanding environment shows how different degrees of credibility can be assigned to alternative concept hypotheses on the basis of such a schema for terminological meta-reasoning.
This work was supported by a grant from DFG under the account Ha2097/2-1.
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Schnattinger, K., Hahn, U., Klenner, M. (1995). Terminological meta-reasoning by reification and multiple contexts. In: Pinto-Ferreira, C., Mamede, N.J. (eds) Progress in Artificial Intelligence. EPIA 1995. Lecture Notes in Computer Science, vol 990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60428-6_1
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DOI: https://doi.org/10.1007/3-540-60428-6_1
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