Differences in the Concept of Fitness Between Artificial Evolution and Natural Selection

Evolutionary algorithms were proposed to automatically find solutions to computational problems, much like evolution discovers new adaptive traits. Lately, they have been used to address challenging questions about the evolution of modularity, the genetic code, communication, division of labor and cooperation. Evolutionary algorithms are increasingly popular in biological studies, because they give precise control over the experimental conditions and allow the study of evolution at unprecedented level of detail. Nevertheless, evolutionary algorithms have their own caveats, which are often overlooked. Here, we highlight one of them by exposing a terminological conflict between definitions of fitness used in biology and in evolutionary algorithms.


Editor(s):
Adami, Christoph
Bryson, David M.
Ofria, Charles
Pennock, Robert T.
Published in:
Artificial Life 13: Proceedings of the Thirteenth International Conference on the Simulation and Synthesis of Living Systems, 530-531
Presented at:
Artificial Life 13, the Thirteenth International Conference on the Simulation and Synthesis of Living Systems, East Lansing, Michigan, USA, July 19-22, 2012
Year:
2012
Publisher:
Cambridge, Massachusetts, The MIT Press
ISBN:
9780262310505
Keywords:
Laboratories:




 Record created 2012-12-17, last modified 2018-03-17

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