Abstract
Some problems related to evolutionary and genetic algorithms, genetic programming, and neural-network computations on solving applied problems that are reduced to analysis of functions prescribed at permutations are roughly studied. Natural parallelism of these algorithms and possibility of their realization on modern computers are noted.
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Original Russian Text © L.N. Korolev, 2007, published in Avtomatika i Telemekhanika, 2007, No. 5, pp. 71–83.
This work was supported by the Russian Foundation for Basic Research, project nos. 06-01-00586 and 06-01-00046, by the program “Leading Scientific Schools,” project no. NSh-4774.2006.1, by the grant of the President of the Russian Federation, project no. MK-1777.2005.1, by INTAS, project no. 05-109-5267, and by the grant of Lavrent’ev Competition for Youth Projects of the Siberian Branch of the Russian Academy of Sciences.
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Korolev, L.N. On evolutionary algorithms, neural-network computations, and genetic programming. Mathematical problems. Autom Remote Control 68, 811–821 (2007). https://doi.org/10.1134/S0005117907050086
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DOI: https://doi.org/10.1134/S0005117907050086