Feature Space Modeling Through Surrogate Illumination
- The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique has the potential to be a powerful tool for design space exploration, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination algorithm (SAIL), introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites. The ability of SAIL to efficiently produce both accurate models and diverse high performing solutions is illustrated on a 2D airfoil design problem. The search space is divided into bins, each holding a design with a different combination of features. In each bin SAIL produces a better performing solution than MAP-Elites, and requires several orders of magnitude fewer evaluations. The CMA-ES algorithm was used to produce an optimal design in each bin: with the same number of evaluations required by CMA-ES to find a near-optimal solution in a single bin, SAIL finds solutions of similar quality in every bin.
Document Type: | Preprint |
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Language: | English |
Author: | Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret |
Number of pages: | 7 |
DOI: | https://doi.org/10.48550/arXiv.1702.03713 |
ArXiv Id: | http://arxiv.org/abs/1702.03713 |
Publisher: | arXiv |
Date of first publication: | 2017/02/14 |
Publication status: | Published in GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference, July 2017, Pages 99–106, https://doi.org/10.1145/3071178.3071282 |
Funding: | This work received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 637972, project ”ResiBots”) and the German Federal Ministry of Education and Research (BMBF) under the Forschung an Fachhochshulen mit Unternehmen programme (grant agreement number 03FH012PX5 project ”Aeromat”). |
Departments, institutes and facilities: | Fachbereich Informatik |
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) | |
Projects: | AErOMAt - Automatisiertes Entwickeln aerodynamischer Strukturen und Fahrzeuge mithilfe evolutionärer Optimierung und Surrogatmodellierung (DE/BMBF/03FH012PX5,13FH012PX5) |
Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Entry in this database: | 2017/03/06 |