Inductive inference theory: a unified approach to problems in pattern recognition and artificial intelligence

Recent results in induction theory are reviewed that demonstrate the general adequacy of the induction system of Solomoncff and Willis. Several problems in pattern recognition and A.I. are investigated through these methods. The theory is used to obtain the a priori probabilities that are necessary in the application cf stochastic languages to pattern recognition. A simple, quantitative solution is presented for part of Winston's problem of learning structural descriptions from exandples. In contrast to work in non-probabilistic prediction, the present methods give probability values that can be used with decision. theory to make critical decisions.

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