Abstract
Since the introduction of cellular automata in the late 1940’s they have been used to address various types of problems in computer science and other multidisciplinary fields. Their generative capabilities have been used for simulating and modelling various natural, physical and chemical phenomena. Besides these applications, the lattice grid of cellular automata has been providing a by-product interface to generate graphical patterns for digital art creation. One important aspect of cellular automata is symmetry, detecting of which is often a difficult task and computationally expensive. In this paper a swarm intelligence algorithm – Stochastic Diffusion Search – is proposed as a tool to identify axes of symmetry in the cellular automata generated patterns.
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Javaheri Javid, M.A., al-Rifaie, M.M., Zimmer, R. (2014). Detecting Symmetry in Cellular Automata Generated Patterns Using Swarm Intelligence. In: Dediu, AH., Lozano, M., Martín-Vide, C. (eds) Theory and Practice of Natural Computing. TPNC 2014. Lecture Notes in Computer Science, vol 8890. Springer, Cham. https://doi.org/10.1007/978-3-319-13749-0_8
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DOI: https://doi.org/10.1007/978-3-319-13749-0_8
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