Output sensitive discretization for genetic algorithm with migration

Szabolcs Kovacs, Gabor J. Toth, Ralf Der, Andras Lorincz

Research output: Contribution to journalArticle

3 Citations (Scopus)


Approximation of unknown input-output mappings by optimizing approximating functions is important for a number of practical applications. A straightforward method involves dividing the whole input space into small regions and finding the optimal approximating value within each. For such a method to work well the way the input region is divided is very important. In this paper we derive an algorithm that takes into account both the distribution of the input points and how rapidly the mapping is changing. The method is demonstrated on a simple function approximation problem.

Original languageEnglish
Pages (from-to)101-107
Number of pages7
JournalNeural Network World
Issue number1
Publication statusPublished - Jan 1 1996


ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Hardware and Architecture
  • Artificial Intelligence

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