Since the introduction of cellular automata in the
late 1940s 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 contents 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
points of symmetry in the cellular automata-generated patterns.