Genetic algorithms: A search technique applied to behavior analysis

Mary K. Dobransky, Mark J. Wierman

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Genetic algorithms are powerful generalized search techniques. This paper shows that genetic algorithms can solve a difficult class of problems in general systems theory quickly and efficiently. Genetic algorithms appear to be ideally suited to solving the combinatorially complex problem of behavior analysis. The search space of behavior analysis experiences exponential growth as a function of the number of variables. The genetic algorithm converges after considering a small percentage of these potential solutions. The number of solutions that need to be examined by the genetic algorithm seems to be a polynomial function of the number of variables and, in fact, the growth appears to be linear.

Original languageEnglish (US)
Pages (from-to)125-135
Number of pages11
JournalInternational Journal of General Systems
Volume24
Issue number1-2
DOIs
StatePublished - Jan 1 1996

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Computer Science Applications

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