Genetic Algorithms in Time-Dependent Environments

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dc.creatorRonnewinkel, Christopher
dc.creatorWilke, Claus O.
dc.creatorMartinetz, Thomas
dc.date1999-11-04
dc.date.accessioned2026-07-07T05:57:26Z
dc.date.available2026-07-07T05:57:26Z
dc.descriptionThe influence of time-dependent fitnesses on the infinite population dynamics of simple genetic algorithms (without crossover) is analyzed. Based on general arguments, a schematic phase diagram is constructed that allows one to characterize the asymptotic states in dependence on the mutation rate and the time scale of changes. Furthermore, the notion of regular changes is raised for which the population can be shown to converge towards a generalized quasispecies. Based on this, error thresholds and an optimal mutation rate are approximately calculated for a generational genetic algorithm with a moving needle-in-the-haystack landscape. The so found phase diagram is fully consistent with our general considerations.
dc.description24 pages, 14 figures, submitted to the 2nd EvoNet Summerschool
dc.identifierhttps://arxiv.org/abs/physics/9911006
dc.identifierhttp://arxiv.org/abs/physics/9911006
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/87984
dc.subjectBiological Physics
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectNeural and Evolutionary Computing
dc.subjectQuantitative Biology
dc.titleGenetic Algorithms in Time-Dependent Environments
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