Local search heuristics: Fitness Cloud versus Fitness Landscape

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dc.creatorCollard, Philippe
dc.creatorVerel, Sébastien
dc.creatorClergue, Manuel
dc.date2007-09-25
dc.date.accessioned2026-07-07T08:32:07Z
dc.date.available2026-07-07T08:32:07Z
dc.descriptionThis paper introduces the concept of fitness cloud as an alternative way to visualize and analyze search spaces than given by the geographic notion of fitness landscape. It is argued that the fitness cloud concept overcomes several deficiencies of the landscape representation. Our analysis is based on the correlation between fitness of solutions and fitnesses of nearest solutions according to some neighboring. We focus on the behavior of local search heuristics, such as hill climber, on the well-known NK fitness landscape. In both cases the fitness vs. fitness correlation is shown to be related to the epistatic parameter K.
dc.identifierhttps://arxiv.org/abs/0709.4010
dc.identifierhttp://arxiv.org/abs/0709.4010
dc.identifierDans Poster at the 2004 European Conference on Artificial Intelligence (ECAI04) - the 2004 European Conference on Artificial Intelligence (ECAI04), Valencia : Espagne (2004)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/138700
dc.subjectArtificial Intelligence
dc.titleLocal search heuristics: Fitness Cloud versus Fitness Landscape
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