Inducing finite state machines from training samples using ant colony optimization

A method for control finite state machine (FSM) induction in which an ant colony opti� mization algorithm is used for search optimization is proposed. The efficiency of this method is esti� mated using the generation of FSMs for controlling a model of an unmanned aerial vehicle (UAV). It is shown that the proposed method outperforms the method based on genetic algorithms both in terms of performance and quality.