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2015 | OriginalPaper | Chapter

Using Evolutionary Algorithms to Personalize Controllers in Ambient Intelligence

Authors : Shu Gao, Mark Hoogendoorn

Published in: Ambient Intelligence - Software and Applications

Publisher: Springer International Publishing

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Abstract

As users can have greatly different preferences, the personalization of ambient devices is of utmost importance. Several approaches have been proposed to establish such a personalization in the form of machine learning or more dedicated knowledge-driven learning approaches. Despite its huge successes in optimization, evolutionary algorithms (EAs) have not been studied a lot in this context, mostly because it is known to be a slow learner. Currently however, quite fast EA based optimizers exist. In this paper, we investigate the suitability of EAs for ambient intelligence.

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Footnotes
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Metadata
Title
Using Evolutionary Algorithms to Personalize Controllers in Ambient Intelligence
Authors
Shu Gao
Mark Hoogendoorn
Copyright Year
2015
Book
Ambient Intelligence - Software and Applications

Print ISBN: 978-3-319-19694-7

Electronic ISBN: 978-3-319-19695-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-19695-4_1

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