Relaxed Genetic Programming
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چکیده
A study on the performance of solutions generated by Genetic Programming (GP) when the training set is relaxed (in order to allow for a wider definition of the desired solution) is presented. This performance is assessed through 2 important features of a solution: its generalization error and its bloat, a common problem of GP individuals. Some encouraging results are presented: we show how even a small degree of relaxation improves the generalization error of the best solutions; we also show how the variation of this parameter reduces the bloat of the solutions generated. General Terms Genetic Programming
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