Abstract
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. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Verel, S., Collard, P., Tomassini, M., & Vanneschi, L. (2006). Neutral fitness landscape in the cellular automata majority problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4173 LNCS, pp. 258–267). Springer Verlag. https://doi.org/10.1007/11861201_31
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
