Abstract
Known methods of automatic generation of finite automata based on genetic programming are inefficient in the case of a large number of input variables of the automaton. A method free from this disadvantage is proposed. The preference of this method for a large number of input variables is theoretically substantiated and experimentally proved. The method was used for automation of development of an aircraft control system on a high level of abstraction.
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