Author(s): C. Jacob
Evolutionary mechanisms as observed in nature are successfully used in evo-
lutionary algorithms (EA) in order to solve complex optimization tasks or to
mimick natural evolution processes.
We present a collection of evolutionary
algorithms which we have implemented in Mathematica together with some
visualization examples and applications.
The three major EA-classes are dis-
cussed: Evolution Strategies (ES), Genetic Algorithms (GA), and Genetic
Interactive evolution is demonstrated by the breeding of
biomorphs, recursively branched line drawings.
Multi-modal ES- and GA-
experiments are demonstrated for a parameter optimization task.
tion of robot control programs shows a simple GP-application.
concludes with a more sophisticated GP-example: the breeding o...
Size: 1,119 kb
Paper DOI: 10.2495/IMS970351
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