Knowledge Acquisition from Structural Descriptions
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE
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The representation of concepts and antecedent-consequent productions is discussed and a method for inducing knowledge by abstracting such representations from a sequence of training examples is described. The proposed learning method, interference matching, induces abstractions by finding relational properties common to two or more exemplars. Three tasks solved by a program which performs an interference matching algorithm are presented. Several problems concerning the relational representation of examples and the induction of knowledge by interference matching are also discussed.
- Computer Programming and Software