
A method for inducing knowledge by abstraction from a sequence of training examples is described. The proposed method, interference matching, induces abstractions by finding relational properties common to two or more exemplars. Three tasks solved by a program that uses an interference-matching algorithm are presented. Several problems concerning the description of the training examples and the adequacy of interference matching are discussed, and directions for future research are considered.
Pattern recognition, speech recognition, Learning and adaptive systems in artificial intelligence, Algorithms in computer science
Pattern recognition, speech recognition, Learning and adaptive systems in artificial intelligence, Algorithms in computer science
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