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Learning Appropriate Contexts

  • Bruce Edmonds
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2116)

Abstract

Genetic Programming is extended so that the solutions being evolved do so in the context of local domains within the total problem domain. This produces a situation where different “species” of solution develop to exploit different “niches” of the problem - indicating exploitable solutions. It is argued that for context to be fully learnable a further step of abstraction is necessary. Such contexts abstracted from clusters of solution/model domains make sense of the problem of how to identify when it is the content of a model is wrong and when it is the context. Some principles of learning to identify useful contexts are proposed.

Keywords

learning conditions of application context evolutionary computing error 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Bruce Edmonds
    • 1
  1. 1.Centre for Policy ModellingManchester Metropolitan UniversityManchesterUK

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