Reducing the Arity in Unbiased Black-Box Complexity
Neural and Evolutionary Computing
2015-03-20 v1
Abstract
We show that for all the -ary unbiased black-box complexity of the -dimensional function class is . This indicates that the power of higher arity operators is much stronger than what the previous bound by Doerr et al. (Faster black-box algorithms through higher arity operators, Proc. of FOGA 2011, pp. 163--172, ACM, 2011) suggests. The key to this result is an encoding strategy, which might be of independent interest. We show that, using -ary unbiased variation operators only, we may simulate an unrestricted memory of size bits.
Cite
@article{arxiv.1203.4111,
title = {Reducing the Arity in Unbiased Black-Box Complexity},
author = {Benjamin Doerr and Carola Winzen},
journal= {arXiv preprint arXiv:1203.4111},
year = {2015}
}
Comments
An extended abstract of this paper has been accepted for inclusion in the proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2012)