Data-Efficient Design Exploration through Surrogate-Assisted Illumination
- Design optimization techniques are often used at the beginning of the design process to explore the space of possible designs. In these domains illumination algorithms, such as MAP-Elites, are promising alternatives to classic optimization algorithms because they produce diverse, high-quality solutions in a single run, instead of only a single near-optimal solution. Unfortunately, these algorithms currently require a large number of function evaluations, limiting their applicability. In this article we introduce a new illumination algorithm, Surrogate-Assisted Illumination (SAIL), that leverages surrogate modeling techniques to create a map of the design space according to user-defined features while minimizing the number of fitness evaluations. On a two-dimensional airfoil optimization problem SAIL produces hundreds of diverse but high-performing designs with several orders of magnitude fewer evaluations than MAP-Elites or CMA-ES. We demonstrate that SAIL is also capable of producing maps of high-performing designs in realistic three-dimensional aerodynamic tasks with an accurate flow simulation. Data-efficient design exploration with SAIL can help designers understand what is possible, beyond what is optimal, by considering more than pure objective-based optimization.
Document Type: | Article |
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Language: | English |
Author: | Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret |
Parent Title (English): | Evolutionary Computation |
Volume: | 26 |
Issue: | 3 |
First Page: | 381 |
Last Page: | 410 |
ISSN: | 1063-6560 |
DOI: | https://doi.org/10.1162/evco_a_00231 |
ArXiv Id: | http://arxiv.org/abs/1806.05865 |
PMID: | https://pubmed.ncbi.nlm.nih.gov/29883202 |
Publisher: | MIT Press |
Date of first publication: | 2018/09/04 |
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 Fachhochschulen mit Unternehmen programme (grant agreement number 03FH012PX5, project "Aeromat"). |
Keyword: | Computer Automated Design; MAP-Elites; Quality Diversity; Surrogate Modeling |
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: | 2018/06/13 |