Evolving Bent Quaternary Functions
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Picek:2018:CEC,
-
author = "Stjepan Picek and Karlo Knezevic and Luca Mariot and
Domagoj Jakobovic and Alberto Leporati",
-
booktitle = "2018 IEEE Congress on Evolutionary Computation (CEC)",
-
title = "Evolving Bent Quaternary Functions",
-
year = "2018",
-
abstract = "Boolean functions have a prominent role in many
real-world applications, which makes them a very active
research domain. Throughout the years, various
heuristic techniques proved to be an attractive choice
for the construction of Boolean functions with
different properties. One of the most important
properties is nonlinearity, and in particular maximally
nonlinear Boolean functions are also called bent
functions. In this paper, instead of considering
Boolean functions, we experiment with quaternary
functions. The corresponding problem is much more
difficult and presents an interesting benchmark as well
as realworld applications. The results we obtain show
that evolutionary metaheuristics, especially genetic
programming, succeed in finding quaternary functions
with the desired properties. The obtained results in
the quaternary domain can also be translated into the
binary domain, in which case this approach compares
favourably with the state-of-the-art in Boolean
optimization. Our techniques are able to find
quaternary bent functions for up to 8 inputs, which
corresponds to obtaining Boolean bent functions of 16
inputs.",
-
keywords = "genetic algorithms, genetic programming, Boolean
functions, cryptography, evolving bent quaternary
functions, active research domain, quaternary domain,
Boolean optimization, quaternary bent functions,
nonlinear Boolean functions, Evolutionary computation",
-
DOI = "doi:10.1109/CEC.2018.8477677",
-
month = jul,
-
notes = "Also known as \cite{8477677}",
- }
Genetic Programming entries for
Stjepan Picek
Karlo Knezevic
Luca Mariot
Domagoj Jakobovic
Alberto Leporati
Citations