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On the Suitability of Representations for Quality Diversity Optimization of Shapes

  • The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in robotic domains has yielded inconsistent results regarding the most appropriate encoding method. Given the domain-dependent nature of QD, additional evidence from other domains is necessary. This study compares the impact of several representations, including direct encoding, a dictionary-based representation, parametric encoding, compositional pattern producing networks, and cellular automata, on the generation of voxelized meshes in an architecture setting. The results reveal that some indirect encodings outperform direct encodings and can generate more diverse solution sets, especially when considering full phenotypic diversity. The paper introduces a multi-encoding QD approach that incorporates all evaluated representations in the same archive. Species of encodings compete on the basis of phenotypic features, leading to an approach that demonstrates similar performance to the best single-encoding QD approach. This is noteworthy, as it does not always require the contribution of the best-performing single encoding.

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Document Type:Conference Object
Author:Ludovico Scarton, Alexander Hagg
Parent Title (English):GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference, Lisbon, Portugal, July 15-19, 2023
Number of pages:9
First Page:963
Last Page:971
Publisher:Association for Computing Machinery
Place of publication:New York, NY, USA
Date of first publication:2023/07/12
Copyright:© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM. Abstracting with credit is permitted.
Keyword:Compositional Pattern Producing Networks; Quality diversity; cellular automata; encoding, representation; parametric
Departments, institutes and facilities:Fachbereich Ingenieurwissenschaften und Kommunikation
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2023/07/17