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Data-Efficient Design Exploration through Surrogate-Assisted Illumination
Abstract : 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 2-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 3-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.
Cited literature [55 references]
https://hal.inria.fr/hal-01817505
Contributor : Jean-Baptiste Mouret <>
Submitted on : Monday, June 18, 2018 - 9:45:03 AM
Last modification on : Tuesday, December 18, 2018 - 4:40:22 PM
Long-term archiving on: : Wednesday, September 26, 2018 - 5:56:03 PM
Contributor : Jean-Baptiste Mouret <>
Submitted on : Monday, June 18, 2018 - 9:45:03 AM
Last modification on : Tuesday, December 18, 2018 - 4:40:22 PM
Long-term archiving on: : Wednesday, September 26, 2018 - 5:56:03 PM
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1806.05865.pdf
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