Stochastic Diffusion Search is an efficient probabilistic best-fit search technique, capable of transformation invariant pattern matching. Although inherently parallel in operation it is difficult to implement efficiently in hardware as it requires full inter-agent connectivity. This paper describes a lattice implementation, which, while qualitatively retaining the properties of the original algorithm, restricts connectivity, enabling simpler implementation on parallel hardware. Diffusion times are examined for different network topologies, ranging from ordered lattices, over small-world networks to random graphs © Springer-Verlag Berlin Heidelberg 2002.
CITATION STYLE
De Meyer, K., Bishop, J. M., & Nasuto, S. J. (2002). Small-world effects in lattice Stochastic Diffusion Search. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2415, 147–152. https://doi.org/10.1007/3-540-46084-5_25
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