Visualization of EC landscape to accelerate EC conversion and evaluation of its effect

We evaluate how visualization of an evolutionary computation (EC) landscape is effective using a geophysical task. This technique allows us to actively participate in EC optimization by viewing the distribution of searching points on 2D space mapped from an n-D EC landscape, and indicating where in the EC is the possible global optimum. We construct a Visualized GA system that includes self-organizing maps for visualization and compare its performance with that of a normal GA using the geophysical simulation task. Sign tests for the comparisons show that the Visualized GA converges significantly faster than the normal EC (p<0.01), which suggests further extensions to enhance user interactivity.