I was hohum about this until I saw the problem it solved in 50 generations with default settings. I'll attach it, but it may get stripped. You can see it at the URL. Also, there's a Python interface that's has recently been released by another author.
-rex http://www.hao.ucar.edu/Public/models/pikaia/pikaia.html Consider an optimization problem that consists of maximizing a function of two variables f(x,y), with x and y bounded between 0 and 1. The function defines a 2-D landscape, in which one is seeking the highest elevation point. If the landscape is smooth and simple this problem is readily treated with conventional hill-climbing methods. However a landscape such as the following would be a much harder task: This is a surface plot of the function f(x,y), and the inset in the upper right is a color-coded version of the same function. The global maximum (indicated by the arrow and located at (x,y)=(0.5,0.5), where f=1) is surrounded by concentric rings of secondary maxima, where a simple hill-climbing method would most likely get stuck. This problem is easily solved with PIKAIA. An individual is an (x,y) pair, and fitness can be directly defined as the altitude in the 2-D landscape, i.e., the value returned by f(x,y). Examination of the corresponding fitness function and driver code shows how simple the use of PIKAIA is for such a problem. The following animation illustrates the evolution of the population's distribution in parameter space. Each individual is shown as a solid green dot, and the best of each generation as a larger, yellow dot. Observe how the ``best solution remains stuck, for a little while, on the innermost ring of secondary extrema, but eventually ``finds'' the thin, central global maximum. The small plot in the upper right shows the variation with generation count of the error (defined as log(1-f) for the best (yellow) and median (purple) individuals in the population. The sudden drops in the error reflect the appearance of a favorable mutation, and its subsequent spread in the population. This solution was obtained by running PIKAIA for 50 generations under its default settings.
pikaia.gif
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