FITNESS FUNCTION CHOOSING FOR GENETIC ALGORITHMS WITH REINFORCEMENT LEARNING
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This paper describes an optimization problem with one target function to be optimized and several supporting functions that can be used to speed up the optimization process. A method based on reinforcement learning is proposed for choosing a good supporting function during optimization using genetic algorithm. Application results of this method to a model problem solution are shown.
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