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Is there anisotropy in structural bias?

Diederick Vermetten, Anna V. Kononova, Fabio Caraffini Orcid Logo, Hao Wang, Thomas Bäck

Proceedings of the Genetic and Evolutionary Computation Conference Companion

Swansea University Author: Fabio Caraffini Orcid Logo

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DOI (Published version): 10.1145/3449726.3463218

Abstract

Structural Bias (SB) is an important type of algorithmic deficiency within iterative optimisation heuristics. However, methods for detecting structural bias have not yet fully matured, and recent studies have uncovered many interesting questions. One of these is the question of how structural bias c...

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Published in: Proceedings of the Genetic and Evolutionary Computation Conference Companion
ISBN: 978-1-4503-8351-6
Published: New York, NY, USA ACM 2021
URI: https://cronfa.swan.ac.uk/Record/cronfa62442
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first_indexed 2023-01-25T17:20:42Z
last_indexed 2023-02-21T04:19:04Z
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spelling 2023-02-20T13:47:05.5321332 v2 62442 2023-01-25 Is there anisotropy in structural bias? d0b8d4e63d512d4d67a02a23dd20dfdb 0000-0001-9199-7368 Fabio Caraffini Fabio Caraffini true false 2023-01-25 SCS Structural Bias (SB) is an important type of algorithmic deficiency within iterative optimisation heuristics. However, methods for detecting structural bias have not yet fully matured, and recent studies have uncovered many interesting questions. One of these is the question of how structural bias can be related to anisotropy. Intuitively, an algorithm that is not isotropic would be considered structurally biased. However, there have been cases where algorithms appear to only show SB in some dimensions. As such, we investigate whether these algorithms actually exhibit anisotropy, and how this impacts the detection of SB. We find that anisotropy is very rare, and even in cases where it is present, there are clear tests for SB which do not rely on any assumptions of isotropy, so we can safely expand the suite of SB tests to encompass these kinds of deficiencies not found by the original tests.We propose several additional testing procedures for SB detection and aim to motivate further research into the creation of a robust portfolio of tests. This is crucial since no single test will be able to work effectively with all types of SB we identify. Conference Paper/Proceeding/Abstract Proceedings of the Genetic and Evolutionary Computation Conference Companion ACM New York, NY, USA 978-1-4503-8351-6 8 7 2021 2021-07-08 10.1145/3449726.3463218 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2023-02-20T13:47:05.5321332 2023-01-25T17:18:03.9585720 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Diederick Vermetten 1 Anna V. Kononova 2 Fabio Caraffini 0000-0001-9199-7368 3 Hao Wang 4 Thomas Bäck 5
title Is there anisotropy in structural bias?
spellingShingle Is there anisotropy in structural bias?
Fabio Caraffini
title_short Is there anisotropy in structural bias?
title_full Is there anisotropy in structural bias?
title_fullStr Is there anisotropy in structural bias?
title_full_unstemmed Is there anisotropy in structural bias?
title_sort Is there anisotropy in structural bias?
author_id_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb
author_id_fullname_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb_***_Fabio Caraffini
author Fabio Caraffini
author2 Diederick Vermetten
Anna V. Kononova
Fabio Caraffini
Hao Wang
Thomas Bäck
format Conference Paper/Proceeding/Abstract
container_title Proceedings of the Genetic and Evolutionary Computation Conference Companion
publishDate 2021
institution Swansea University
isbn 978-1-4503-8351-6
doi_str_mv 10.1145/3449726.3463218
publisher ACM
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
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description Structural Bias (SB) is an important type of algorithmic deficiency within iterative optimisation heuristics. However, methods for detecting structural bias have not yet fully matured, and recent studies have uncovered many interesting questions. One of these is the question of how structural bias can be related to anisotropy. Intuitively, an algorithm that is not isotropic would be considered structurally biased. However, there have been cases where algorithms appear to only show SB in some dimensions. As such, we investigate whether these algorithms actually exhibit anisotropy, and how this impacts the detection of SB. We find that anisotropy is very rare, and even in cases where it is present, there are clear tests for SB which do not rely on any assumptions of isotropy, so we can safely expand the suite of SB tests to encompass these kinds of deficiencies not found by the original tests.We propose several additional testing procedures for SB detection and aim to motivate further research into the creation of a robust portfolio of tests. This is crucial since no single test will be able to work effectively with all types of SB we identify.
published_date 2021-07-08T04:22:04Z
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score 10.998116

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