@inproceedings{HaggAsterothBaeck2018, author = {Alexander Hagg and Alexander Asteroth and Thomas B{\"a}ck}, title = {Prototype Discovery Using Quality-Diversity}, series = {Auger, Fonseca et al. (Eds.): Parallel Problem Solving from Nature – PPSN XV (PPSN 2018). Lecture Notes in Computer Science, vol 11101}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-99252-5}, doi = {10.1007/978-3-319-99253-2\_40}, pages = {500 -- 511}, year = {2018}, abstract = {An iterative computer-aided ideation procedure is introduced, building on recent quality-diversity algorithms, which search for diverse as well as high-performing solutions. Dimensionality reduction is used to define a similarity space, in which solutions are clustered into classes. These classes are represented by prototypes, which are presented to the user for selection. In the next iteration, quality-diversity focuses on searching within the selected class. A quantitative analysis is performed on a 2D airfoil, and a more complex 3D side view mirror domain shows how computer-aided ideation can help to enhance engineers' intuition while allowing their design decisions to influence the design process.}, language = {en} }