On Using Surrogates with Genetic Programming


One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical… (More)
DOI: 10.1162/EVCO_a_00133


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