In domains where a stochastic process is involved in the evaluation of a candidate solution, multiple evaluations are necessary to obtain a good estimate of the performance of an individual. This work shows that biasing the sampling of that problem configuration space can lead to better performance of the structure being learned given the same amount of effort. (AN)