Improving Strategy Parameters of Evolutionary Computations with Interactive Coordinated Views

A. Kerren (Germany)


Information Visualization, Software Visualization, Evolu tionary Algorithms, Coordinated Views, HCI


Evolutionary algorithms (EAs) use mechanisms inspired by biological evolution, e.g., natural selection, recombina tion, or mutation, that work on populations of solutions for a speciļ¬c problem. These recurring processes produce a huge amount of time-varying data. In order to get a bet ter insight into the progress of EAs, a Java-based visualiza tion tool, called EAVis, was developed. The most important aims of EAVis are the selection, concentration, and abstrac tion of evolutionary data on different levels using a variety of visualization methods. Several coordinated views (2D and 3D) help the user to watch each generation step of the EA and to derive knowledge as well as better understand ing of the underlying evolutionary computational models. Among other things, this is also important for a clever pa rameter setting to gain better performance values.

Important Links:

Go Back