Learning: The Construction of A Posteriori Knowledge Structures

Paul D. Scott

This paper is a critical examination of both the nature of learning and its value in artificial intelligence. After examining alternative definitions it is concluded that learning is in fact any process for the acquisition of synthetic a posteriori knowledge structures. The suggestion that learning will not prove useful in machines is examined and it is argued. that its main application in practical Al systems terns is in providing a means by which a system can acquire knowledge which is not readily formalizable. Finally some of the implications of these conclusions for future Al research are explored.

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