Daniel Ashlock
Further Exploration of Necrotic Control of Evolved Art
Ashlock, Daniel; Greensmith, Julie
Abstract
This study is the second in investigating the use of necrosis based filtration as a method of steering evolutionary algorithms to create evolved art. We use a technique inspired by the danger theory of immune system activation - a method employed in Artificial Immune Systems. An earlier study tested two types of filters used to augment the evolution of apoptotic cellular automata, shape and state diversity, applying one as a soft filter and the other as a crisp filter. This study tests both shape and state diversity filters in both soft and crispmodes and also mixes the filters, applying two filters in a single evolutionary algorithm. Soft and crisp version of the same filterare found to have substantially different behavior. The stacking of filters is found to work simply and transparently, effectively excluding undesirable parts of the fitness landscape.
Citation
Ashlock, D., & Greensmith, J. (2020, December). Further Exploration of Necrotic Control of Evolved Art. Presented at 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, ACT, Australia
Presentation Conference Type | Edited Proceedings |
---|---|
Conference Name | 2020 IEEE Symposium Series on Computational Intelligence (SSCI) |
Start Date | Dec 1, 2020 |
End Date | Dec 4, 2020 |
Acceptance Date | Sep 30, 2020 |
Online Publication Date | Jan 5, 2021 |
Publication Date | Dec 1, 2020 |
Deposit Date | Nov 10, 2020 |
Publicly Available Date | Dec 1, 2020 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 2957-2964 |
Book Title | Proceedings - 2020 IEEE Symposium Series on Computational Intelligence (SSCI) |
ISBN | 978-1-7281-2548-0 |
DOI | https://doi.org/10.1109/SSCI47803.2020.9308363 |
Public URL | https://nottingham-repository.worktribe.com/output/5032873 |
Publisher URL | https://ieeexplore.ieee.org/document/9308363 |
Related Public URLs | http://www.ieeessci2020.org/index.html |
Additional Information | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works |
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