| Summary: | Stochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelligence algorithms.
In contrast to many nature-inspired algorithms, stochastic diffusion search has a strong mathematical framework
describing its behaviour and convergence. In addition to concisely exploring the algorithm in the context of natural
swarm intelligence systems, this paper reviews various developments of the algorithm, which have been shown to
perform well in a variety of application domains including continuous optimisation, implementation on hardware and
medical imaging. This algorithm has also being utilised to argue the potential computational creativity of swarm
intelligence systems through the two phases of exploration and exploitation.
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