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Fundamental mechanisms in machine learning and inductive inference

  • Alan W. Biermann
Part Two Knowledge Processing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 232)

Abstract

Computer science has historically required programmers of systems to anticipate every possible behavior that could be desired and to program in advance all the knowledge and mechanisms needed to achieve it. Unfortunately, it has been found that such extensive and explicit programing is expensive and it still, in many cases, does not achieve the range of behaviors that might be needed. The only alternative is to have the machines program themselves to acquire the knowledge they need to function satisfactorily. This chapter has described many mechanisms for machine learning and provides an introduction to the field. Additional information can be found in the references and in the textbook on learning edited by Michalski et al. [83].

Keywords

Turing Machine Positive Information Inductive Inference Disjunctive Normal Form Prolog Program 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  • Alan W. Biermann
    • 1
  1. 1.Duke UniversityDurham

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