Parsimonious Representation of Knowledge Uncertainty using Metadata about Validity and Completeness
Abstract
We investigate how metadata about the uncertainty of knowledge contained in a knowledge base can be expressed parsimoniously and used for reasoning. We propose an approach based on possibility theory, whereby a classical knowledge base plus metadata about the degree of validity and completeness of some of its portions are used to represent a possibilistic belief base. We show how reasoning on such belief base can be done using a classical reasoner.
Domains
Artificial Intelligence [cs.AI]
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