Neutral Fitness Landscape in the Cellular Automata Majority Problem
  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. 
S\'ebastien Verel (I3S), Philippe Collard (I3S), Marco Tomassini   (ISI), Leonardo Vanneschi (ISI)