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Algorithmic learning from incomplete information: Principles and problems

  • Klaus P. Jantke
Chapter 4 Artificial Intelligence
Part of the Lecture Notes in Computer Science book series (LNCS, volume 381)

Keywords

Incomplete Information Infinite Sequence Inductive Inference Identification Type Ground Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. /01/.
    Dana Angluin and Carl Smith, A survey of inductive inference: theory and methods, Computing Surveys 15 (1983), 237–269Google Scholar
  2. /02/.
    E. Mark Gold, Language identification in the limit, Information and Control 14 (1967), 447–474Google Scholar
  3. /03/.
    Klaus P. Jantke and Hans-Rainer Beick, Combining postulates of naturalness in inductive inference, EIK 17 (1981) 8/9, 465–484Google Scholar
  4. /04/.
    Reinhard Klette and Rolf Wiehagen, Research in the theory of inductive inference by GDR mathematicians — a survey, Inf. Sciences 22 (1980), 149–169Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Klaus P. Jantke
    • 1
  1. 1.Dept. of Mathematics & InformaticsLeipzig University of TechnologyLeipzigDDR

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