Nĕmečková, I.; James-Reynolds, C.; Currie, E.

Evolutionary art with an EEG fitness function

Conference paper

Nĕmečková, I., James-Reynolds, C. and Currie, E. 2019. Evolutionary art with an EEG fitness function. Bramer, M. and Petridis, M. (ed.) AI-2019 Thirty-ninth SGAI International Conference on Artificial Intelligence. Cambridge, United Kingdom 17 - 19 Dec 2019 Springer. pp. 241-252 https://doi.org/10.1007/978-3-030-34885-4_19

ISBN
Type	Conference paper
Title	Evolutionary art with an EEG fitness function
Authors	Nĕmečková, I., James-Reynolds, C. and Currie, E.
Abstract	This project involved the use of an interactive Genetic Al-gorithm (iGA) with an electroencephalogram (EEG)-based fitness function to create paintings in the style of Piet Mondrian, a Dutch painter who used geometric elements in his later paintings. Primary data for the prototype was gathered by analysis of twenty-seven existing Mondrian paintings. An EEG gaming headset was used to read EEG signals, which were transmitted by Bluetooth to an Arduino running an iGA. These values were used as the iGA fitness function. The data was sent to a PC running Processing to dis-play the artwork. The resultant displayed artwork evolves to favour higher attention and meditation levels, which are considered to represent greater mindfulness. The process ends when the observer identifies a piece of art they would like to keep. However, convergence of the algorithm is difficult to test as many parameters can affect the process. A number of issues aris-ing from the research are discussed and further work is proposed.
Research Group	Artificial Intelligence group
Conference	AI-2019 Thirty-ninth SGAI International Conference on Artificial Intelligence
Page range	241-252
Proceedings Title	Artificial Intelligence XXXVI: 39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceedings
Series	Lecture Notes in Computer Science
Editors	Bramer, M. and Petridis, M.
ISSN	0302-9743
Electronic	1611-3349
Hardcover	9783030348847
Electronic	9783030348854
Publisher	Springer
Publication dates
Online	19 Nov 2019
Publication process dates
Deposited	21 Oct 2019
Accepted	05 Sep 2019
Output status	Published
Accepted author manuscript	Mondrian Final Version after comments sent.pdf File Access Level Open
Copyright Statement	The final authenticated version is available online at https://doi.org/10.1007/978-3-030-34885-4_19
Additional information	Proceedings part of the Lecture Notes in Computer Science book series (LNCS, volume 11927) Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 11927)
Digital Object Identifier (DOI)	https://doi.org/10.1007/978-3-030-34885-4_19
Web address (URL) of conference proceedings	https://doi.org/10.1007/978-3-030-34885-4
Language	English

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File access level: Open

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