We study in detail the fitness landscape of a difficult cellular automata computational task: the majority problem. Our results show why this problem landscape is so hard to search, and we quantify the large degree of neutrality found in various ways. We show that a particular subspace of the solution space, called the "Olympus", is where good solutions concentrate, and give measures to quantitatively characterize this subspace.
Cite
@article{arxiv.0803.4240,
title = {Neutral Fitness Landscape in the Cellular Automata Majority Problem},
author = {Sébastien Verel and Philippe Collard and Marco Tomassini and Leonardo Vanneschi},
journal= {arXiv preprint arXiv:0803.4240},
year = {2008}
}