@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}
}