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**1 - 4**of**4**### Evolutionary and Complex Systems Group

"... Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources are tree nodes or code lines. We elaborate on this recent concept, introducing a dynamic approach to managing the amount ..."

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Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources are tree nodes or code lines. We elaborate on this recent concept, introducing a dynamic approach to managing the amount of resources available for each generation. Initially low, this amount is increased only if it results in better population fitness. We compare the dynamic approach to the static method where a constant amount of resources is available throughout the run, and with the most traditional usage of a depth limit at the individual level. The dynamic approach does not impair performance on the Symbolic Regression of the quartic polynomial, and achieves excellent results on the Santa Fe Artificial Ant problem, obtaining the same fitness with only a small percentage of the computational effort demanded by the other techniques.

### General Terms Genetic Programming

"... 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 bl ..."

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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.

### Program Synthesis General Terms

"... 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 bl ..."

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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. We show how a small degree of relaxation improves the generalization error of the best solutions; we also show how the variation of this parameter affects the bloat of the solutions generated.