On the design of state-of-the-art pseudorandom number
generators by means of genetic programming
Proceedings of the 2004 IEEE Congress on Evolutionary
Computation, page 1510--1516. Portland, Oregon, IEEE Press, (20-23 June 2004)Abstract
The design of pseudorandom number generators by means
of evolutionary computation is a classical problem. To
day, it has been mostly and better accomplished by
means of cellular automata and not many proposals,
inside or outside this paradigm, could claim to be both
robust (passing many statistical tests, including the
most demanding ones) and fast, as is the case of the
proposal we present. Furthermore, we use a radically
new approach, where our fitness function is not at all
based in any measure of randomness, as is frequently
the case in the literature, but of non-linearity.
Efficiency is assured by using only very efficient
operators, and by limiting the number of terminals in
the Genetic Programming implementation.