Prototype Discovery Using Quality-Diversity

  • 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.

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Metadaten
Document Type:Conference Object
Language:English
Parent Title (English):Auger, Fonseca et al. (Eds.): Parallel Problem Solving from Nature – PPSN XV. PPSN 2018. Lecture Notes in Computer Science, vol 11101
First Page:500
Last Page:511
ISBN:978-3-319-99252-5
DOI:https://doi.org/10.1007/978-3-319-99253-2_40
ArXiv Id:http://arxiv.org/abs/1807.09488
Publisher:Springer
Place of publication:Cham
Date of first publication:2018/08/22
Tag:dimensionality reduction; ideation; prototype theory; quality-diversity
Departments, institutes and facilities:Fachbereich Informatik
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Dewey Decimal Classification (DDC):000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2018/08/10