Towards optimisers that 'Keep Learning'

Emma Hart, Ian Miguel, Christopher Stone, Quentin Renau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider optimisation in the context of the need to apply an optimiser to a continual stream of instances from one or more domains, and consider how such a system might 'keep learning': by drawing on past experience to improve performance and learning how to both predict and react to instance and/or domain drift.
Original languageEnglish
Title of host publicationGECCO '23 companion
Subtitle of host publicationproceedings of the companion conference on genetic and evolutionary computation
EditorsSara Silva
Place of PublicationNew York, NY
PublisherACM
Pages1636-1638
Number of pages3
ISBN (Electronic)9798400701207
DOIs
Publication statusPublished - 24 Jul 2023

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