A new evolution scheme is presented, memorizing the extreme (best and worst) past individuals through distributions over the binary search space. These distributions are used to bias the mutation operator in a (μ + λ) Evolution Strategy, guiding the generation of newborn offspring: different mimetic strategies are defined, combining either attraction, indifference or repulsion with respect to the two distributions. These distributions are then updated from the best and the worse individuals in the current population. Experiments on large size binary problems allow one to delineate the niche of each of these mimetic strategies.