Experiments in Genetic Divergence for Emergent Systems

McGowan, Christopher and Wild, Alexander and Porter, Barry Francis (2018) Experiments in Genetic Divergence for Emergent Systems. In: GI '18 Proceedings of the 4th International Workshop on Genetic Improvement Workshop. ACM, pp. 9-16. ISBN 9781450357531

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Abstract

Emergent software systems take a step towards tackling the ever-increasing complexity of modern software, by having systems self-assemble from a library of building blocks, and then continually re-assemble themselves from alternative building blocks to learn which compositions of behaviour work best in each deployment environment. One of the key challenges in emergent systems is populating the library of building blocks, and particularly a set of alternative implementations of particular building blocks, which form the runtime search space of optimal behaviour. We present initial work in using a fusion of genetic improvement and genetic synthesis to automatically populate a divergent set of implementations of the same functionality, allowing emergent systems to explore new behavioural alternatives without human input. Our early results indicate this approach is able to successfully yield useful divergent implementations of building blocks which are more suited than any existing alternative for particular operating conditions.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
© ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in GI '18 Proceedings of the 4th International Workshop on Genetic Improvement Workshop, 2018 10.1145/3194810.3194813
ID Code:
124101
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Deposited On:
19 Mar 2018 10:52
Refereed?:
Yes
Published?:
Published
Last Modified:
29 Sep 2020 06:24