Javaheri Javid, Mohammad Ali, Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 and Zimmer, Robert (2015) Swarm intelligence approach in detecting spatially-independent symmetries in cellular automata. In: 2015 SAI Intelligent Systems Conference (IntelliSys). IEEExplore . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, US, pp. 632-639. ISBN 978-1467376068 (doi:https://doi.org/10.1109/IntelliSys.2015.7361206)

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Abstract

In late 1940's and with the introduction of cellular automata, various types of problems in computer science and other multidisciplinary fields have started utilising this new technique. The generative capabilities of cellular automata have been used for simulating various natural, physical and chemical phenomena. Aside from these applications, the lattice grid of cellular automata has been providing a by-product interface to generate graphical patterns for digital art creation. One notable aspect of cellular automata is symmetry, detecting of which is often a difficult task and computationally expensive. This paper uses a swarm intelligence algorithm - Stochastic Diffusion Search - to extend and generalise previous works and detect partial symmetries in cellular automata generated patterns. The newly proposed technique tailored to address the spatially-independent symmetry problem is also capable of identifying the absolute point of symmetry (where symmetry holds from all perspectives) in a given pattern. Therefore, along with partially symmetric areas, the centre of symmetry is highlighted through the convergence of the agents of the swarm intelligence algorithm. This technique is potentially applicable in the domain of aesthetic evaluation where symmetry is one of the measures.

Item Type:	Conference Proceedings
Title of Proceedings:	2015 SAI Intelligent Systems Conference (IntelliSys)
Uncontrolled Keywords:	cellular automata, stochastic diffusion search, symmetry
Subjects:	B Philosophy. Psychology. Religion > BH Aesthetics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Related URLs:	Publisher
Last Modified:	04 Mar 2022 13:07
URI:	http://gala.gre.ac.uk/id/eprint/21014

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