Computational evolution taking liberties

Authors: Luís Correia

Publish Date: 2010/06/09

Volume: 129, Issue: 2-3, Pages: 183-191

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Abstract

Evolution has for a long time inspired computer scientists to produce computer models mimicking its behavior Evolutionary algorithm EA is one of the areas where this approach has flourished EAs have been used to model and study evolution but they have been especially developed for their aptitude as optimization tools for engineering Developed models are quite simple in comparison with their natural sources of inspiration However since EAs run on computers we have the freedom especially in optimization models to test approaches both realistic and outright speculative from the biological point of view In this article we discuss different common evolutionary algorithm models and then present some alternatives of interest These include biologically inspired models such as coevolution and in particular symbiogenetics and outright artificial operators and representations In each case the advantages of the modifications to the standard model are identified The other area of computational evolution which has allowed us to study basic principles of evolution and ecology dynamics is the development of artificial life platforms for openended evolution of artificial organisms With these platforms biologists can test theories by directly manipulating individuals and operators observing the resulting effects in a realistic way An overview of the most prominent of such environments is also presented If instead of artificial platforms we use the real world for evolving artificial life then we are dealing with evolutionary robotics ERs A brief description of this area is presented analyzing its relations to biology Finally we present the conclusions and identify future research avenues in the frontier of computation and biology Hopefully this will help to draw the attention of more biologists and computer scientists to the benefits of such interdisciplinary research

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