Data-efficient exploration, optimization, and modeling of diverse designs through surrogate-assisted illumination
Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret · Proceedings of the Genetic and Evolutionary Computation Conference · 2017
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique to 'illuminate' the problem space through the lens of chosen features has the potential to be a powerful tool for exploring design spaces, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination (SAIL) algorithm, introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites.