Neutral Fitness Landscape in the Cellular Automata Majority Problem

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dc.creatorVerel, Sébastien
dc.creatorCollard, Philippe
dc.creatorTomassini, Marco
dc.creatorVanneschi, Leonardo
dc.date2008-03-29
dc.date.accessioned2026-07-07T12:17:57Z
dc.date.available2026-07-07T12:17:57Z
dc.descriptionWe 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.
dc.identifierhttps://arxiv.org/abs/0803.4240
dc.identifierhttp://arxiv.org/abs/0803.4240
dc.identifierDans ACRI 2006 - 7th International Conference on Cellular Automata For Research and Industry - ACRI 2006, France (2006)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212249
dc.subjectNeural and Evolutionary Computing
dc.titleNeutral Fitness Landscape in the Cellular Automata Majority Problem
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