Abstract:
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This paper introduces a formal base in order to talk about theory learning from a Description Logics (DL) perspective. A
probabilistic Description Logics is introduced; and its need is intuitively justified. Theory learning is defined using information
theory concepts and the probabilistic DL framework. Once this has been done, a general theory learning environment is
constructed on this theory. This environment is based on the application of a set of induction rules. New rules can be defined
easily using a set of syntactic manipulators that modify concept expressions. |