Learning to Predict Non-Deterministically Generated Strings

  • Authors:

  • Moshe Koppel

  • Affiliations:

  • Department of Math and Computer Science, Bar-Ilan University, 52 900 Ramat-Gan, Israel

  • Venue:
  • Machine Learning
  • Year:
  • 1991

  • Sophistication revisited

    ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming

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Abstract

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.