Conference Paper/Proceeding/Abstract 917 views 180 downloads
Using structural bias to analyse the behaviour of modular CMA-ES
,
Bas van Stein,
Anna V. Kononova
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Swansea University Author:
Fabio Caraffini
-
PDF | Version of Record
© 2022 Copyright held by the owner/author(s). Released under the terms of a CC-BY License
Download (2.36MB)
DOI (Published version): 10.1145/3520304.3534035
Abstract
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a commonly used iterative optimisation heuristic for optimising black-box functions. CMA-ES comes in many flavours with different configuration settings. In this work, we investigate whether CMA-ES suffers from structural bias and which...
| Published in: | Proceedings of the Genetic and Evolutionary Computation Conference Companion |
|---|---|
| ISBN: | 978-1-4503-9268-6 |
| Published: |
New York, NY, USA
ACM
2022
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa62444 |
| Abstract: |
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a commonly used iterative optimisation heuristic for optimising black-box functions. CMA-ES comes in many flavours with different configuration settings. In this work, we investigate whether CMA-ES suffers from structural bias and which modules and parameters affect the strength and type of structural bias. Structural bias occurs when an algorithm or a component of the algorithm biases the search towards a specific direction in the search space irrespective of the objective function. In addition to this investigation, we propose a method to assess the relationship between structural bias and the performance of configurations with different types of bias on the BBOB suite of benchmark functions. Surprisingly for such a popular algorithm, 90.3% of the 1 620 CMA-ES configurations were found to have Structural Bias. Some interesting patterns between module settings and bias types are presented and further insights are discussed. |
|---|---|
| College: |
Faculty of Science and Engineering |