Learning to Predict Non-Deterministically Generated Strings
作者:Moshe Koppel
摘要
In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.
论文关键词:Prediction, Kolmogorov complexity, minimum description length, learning in the limit
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论文官网地址:https://doi.org/10.1023/A:1022671126433