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Evolutionary computations, (the synonym in Russian literature is «эволюционные вычисления») proved its efficiency for either solving hardly formalizing problems of artificial intelligence (patter recognition, clasterization, associative search) nor for solving labor-consuming optimization, approximation and intelligent treatment tasks. Advantages of evolutionary systems include adaptiveness, learning capability, parallelism, possibility to create hybrid intellectual systems based on combination of neural network and fuzzy logic paradigms. Presumption of creating single evolutionary computation conception including genetic algorithms, genetic programming, evolutionary strategies and programming, looks very promising. Many researchers think that these paradigms are being analogue of processes, taking place in nature and proved its complexity in practice. The pioneer of evolutionary computations L. Fogel seems the theory of evolution and self-organization like concept for all intellectual systems and processes, greatly extending usual influence area of traditional artificial intelligence paradigm. Even if it is wrong and degradation take place in nature, nobody can say that evolutionary algorithms are wrong.