This paper proposes the employment of continuous probability distributions instead of step functions for adaptive coordination of the local search in fitness diversity based memetic algorithms. Two probability distributions are considered in this study: the beta and exponential distributions. These probability distributions have been tested within two memetic frameworks present in literature. Numerical results show that employment of the probability distributions can be beneficial and improve performance of the original memetic algorithms on a set of test functions without varying the balance between the evolutionary and local search components.