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Evolutionary Computation - A Study on Collective Learning

dc.contributor.authorSchwefel, Hans-Paulde
dc.date.accessioned2004-12-07T08:19:16Z
dc.date.available2004-12-07T08:19:16Z
dc.date.created1997de
dc.date.issued1998-11-08de
dc.description.abstractOn the one hand, people admire the often strikingly efficient results of organic evolution. On the other hand, however, they decry mutation and selection to be a rather prodigal, inefficient trial-and-error strategy. Taking into account the parallel information processing in a heterogeneous population and sexual propagation with recombination as well as the genetic control of the reproduction accuracy, computer simulated evolution reveals a couple of interesting, sometimes surprising, properties of nature's learning by-doing algorithm. Survival of the fittest, Spencer's resume of Darwin's view, turns out to be a bad advice if taken literally. Individual death, forgetting, and even regression show up to be necessary ingredients of the life game. Whether the process should be named gradualistic or punctualistic, is a matter of the observer's point of view.en
dc.format.extent159214 bytes
dc.format.extent215803 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/5324
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15254
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 13de
dc.subject.ddc004de
dc.titleEvolutionary Computation - A Study on Collective Learningen
dc.typeTextde
dc.type.publicationtypereport
dcterms.accessRightsopen access
eldorado.dnb.deposittrue

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