DESIGN OF A SURROGATE ASSISTED (1 + 1)-ES
Date
2018-12-14T18:00:02Z
Authors
Kayhani, Arash
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Abstract
The information gained from previous iterations of an evolution strategy (ES) can be used to create a surrogate model based on the real objective function. While surrogate models are not as accurate as objective functions, they could distinguish more promising candidate solutions. To develop a better understanding of surrogate-assisted ESs, we simulate the behavior of a surrogate-assisted (1 + 1)-ES on the quadratic sphere. These simulations are made using a noisy objective function as the surrogate model. We introduce some measures to quantify the trade-off of saving expensive objective function evaluations at the cost of taking poorer steps. Using these findings, we present a mechanism to adapt the step-size based on model accuracy. We empirically evaluate the performance of this step-size adaptation mechanism in surrogate-assisted (1 + 1)-ES and compare it to that of the canonical (1 + 1)-ES on several simple test functions.
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Keywords
Surrogate-assisted evolution strategy