Analyzing active interactive genetic algorithms using visual analytics

by Xavier Llorà, Kumara Sastry , Francesc Alías, David E. Goldberg, and Michael Welge (2006).

Proceedings of the ACM Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 1417–1418, ACM press. Also as IlliGAL TR No 2006004. Link to the PDF.

Abstract

This paper build on active interactive genetic algorithms and introduces visual-analytic techniques to aggregate, summarize, and visualize the information generated during interactive evolutionary processes. Special visualizations of the user-provided partial ordering of solutions, the synthetic fitness surrogates induced, and the model of user preferences were prepared. The visual-analytic techniques proposed point out potential pitfalls, strengths, and possible improvements in a non-trivial case study where the hierarchical tournament selection scheme of an active interactive genetic algorithm is replaced by an equivalent incremental selection scheme. Visual analytics provided an intuitive reasoning environment that unveiled important properties that greatly affect the performance of active interactive genetic algorithms that could not have been easily reveled otherwise.