  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.
