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Automation and Remote Control

, Volume 62, Issue 10, pp 1698–1710 | Cite as

Genetic Search-Based Control

  • V. V. Kureichik
  • V. M. Kureichik
Article

Abstract

Control in intelligent systems which handle the optimizational decision support problems was considered. A new line of research, modeling of evolution and genetic search, was proposed for it. The main principles of evolution in artificial systems were studied. Strategies of interaction of the search methods and evolutionary modeling were presented. Nonstandard control architectures for solving the optimizational decision support problems were constructed, which enables one to parallelize the process of search of the optimizational decision support problems and obtain the set of local optima in a polynomial time. Complexity of the algorithms has a quadratic order.

Keywords

Mechanical Engineer Decision Support System Theory Evolutionary Modeling Polynomial Time 
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

© MAIK “Nauka/Interperiodica” 2001

Authors and Affiliations

  • V. V. Kureichik
    • 1
  • V. M. Kureichik
    • 1
  1. 1.Taganrog State Radio Engineering UniversityTaganrogRussia

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