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Swarmic paintings and colour attention

Swarmic paintings and colour attention

Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 and Bishop, Mark (2013) Swarmic paintings and colour attention. In: Evolutionary and Biologically Inspired Music, Sound, Art and Design Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, 2013. Proceedings. Lecture Notes in Computer Science book series (LNCS), 7834 . Springer, Berlin, Germany, pp. 97-108. ISBN 978-3642369544 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:https://doi.org/10.1007/978-3-642-36955-1_9)

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Abstract

Swarm-based multi-agent systems have been deployed in non-photorealistic rendering for many years. This paper introduces a novel approach in adapting a swarm intelligence algorithm – Stochastic Diffusion Search – for producing non-photorealistic images. The swarm-based system is presented with a digital image and the agents move throughout the digital canvas in an attempt to satisfy the dynamic roles – attention to different colours - associated to them via their fitness function. Having associated the rendering process with the concepts of ‘attention’ in general and colour attention in particular, this papers briefly discusses the ‘computational creativity’ of the work through two prerequisites of creativity (i.e. freedom and constraints) within the swarm intelligence’s two infamous phases of exploration and exploitation.

Item Type: Conference Proceedings
Title of Proceedings: Evolutionary and Biologically Inspired Music, Sound, Art and Design Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, 2013. Proceedings
Uncontrolled Keywords: Stochastic diffusion search; swarm intelligence; computational creativity
Subjects: B Philosophy. Psychology. Religion > BH Aesthetics
M Music and Books on Music > M Music
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Computer & Computational Science
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 21 Jul 2021 13:11
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/21026

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