On the design of state-of-the-art pseudorandom number generators by means of genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7917

@InProceedings{hernandez:2004:otdospngbmogp,

• title = "On the design of state-of-the-art pseudorandom number generators by means of genetic programming",
• author = "Julio Cesar Hernandez and Andre Seznec and Pedro Isasi",
• pages = "1510--1516",
• booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
• year = "2004",
• publisher = "IEEE Press",
• month = "20-23 " # jun,
• address = "Portland, Oregon",
• ISBN = "0-7803-8515-2",
• DOI = "doi:10.1109/CEC.2004.1331075",
• keywords = "genetic algorithms, genetic programming, Evolutionary Computation in Cryptology and Computer Security, cellular automata, fitness function, pseudorandom number generators, cellular automata, random number generation",
• 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.",
• notes = "PRNG. Also known as \cite{1331075}. CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Julio Cesar Hernandez-Castro Andre Seznec Pedro Isasi Vinuela

Citations