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Matematicheskaya Biologiya i Bioinformatika, 2014, Volume 9, Issue Suppl., Pages t1–t15
DOI: https://doi.org/10.17537/2014.9.t1
(Mi mbb323)
 

Translations of Published Articles

The model of interaction between learning and evolutionary optimization

V. G. Red'ko

Scientific Research Institute for System Analysis, Russian Academy of Sciences, Moscow, 117218, Russia
References:
Abstract: The model of interaction between learning and evolutionary optimization is designed and investigated. The evolving population of modeled organisms is considered. The mechanism of genetic assimilation of the acquired features during a number of generations of Darwinian evolution is studied. The genetic assimilation means that individually acquired features are “re-invented” by evolution and recorded directly into genotypes of organisms. It is shown that the genetic assimilation takes place as follows: the organism distribution moves towards the optimum at learning and further selection; then genotypes of selected organisms also move towards the optimum. The mechanism of influence of the learning load is analyzed. It is shown that the learning load leads to a significant acceleration of evolution. The hiding effect is also studied; this effect means that a strong learning inhibits the evolutionary search in some situations.
Key words: speed and efficiency of evolutionary search, Baldwin effect, genetic assimilation, hiding effect, learning load.
Funding agency Grant number
Russian Foundation for Basic Research 10-01-00129_à
Russian Academy of Sciences - Federal Agency for Scientific Organizations
This work is partially supported by the Russian Foundation for Basic Research, Grant No 10-01-00129 and the Program by the Presidium of the Russian Academy of Science “Intelligent informational technologies, mathematical modeling, system analysis and automatization”.
Received 22.04.2014, Published 19.08.2014
Document Type: Article
UDC: 32.81
Language: English
Citation: V. G. Red'ko, “The model of interaction between learning and evolutionary optimization”, Mat. Biolog. Bioinform., 9, Suppl. (2014), t1–t15
Citation in format AMSBIB
\Bibitem{Red14}
\by V.~G.~Red'ko
\paper The model of interaction between learning and evolutionary optimization
\jour Mat. Biolog. Bioinform.
\yr 2014
\vol 9
\pages t1--t15
\issueinfo Suppl.
\mathnet{http://mi.mathnet.ru/mbb323}
\crossref{https://doi.org/10.17537/2014.9.t1}
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