Influences on the formation and evolution of Physarum polycephalum inspired emergent transport networks

Jones, Jeff

Abstract

The single-celled organism Physarum polycephalum efficiently constructs and minimises dynamical nutrient transport networks resembling proximity graphs in the Toussaint hierarchy. We present a particle model which collectively approximates the behaviour of Physarum. We demonstrate spontaneous transport network formation and complex network evolution using the model and show that the model collectively exhibits quasi-physical emergent properties, allowing it to be considered as a virtual computing material. This material is used as an unconventional method to approximate spatially represented geometry problems by representing network nodes as nutrient sources. We demonstrate three different methods for the construction, evolution and minimisation of Physarum-like transport networks which approximate Steiner trees, relative neighbourhood graphs, convex hulls and concave hulls. We extend the model to adapt population size in response to nutrient availability and show how network evolution is dependent on relative node position (specifically inter-node angle), sensor scaling and nutrient concentration. We track network evolution using a real-time method to record transport network topology in response to global differences in nutrient concentration. We show how Steiner nodes are utilised at low nutrient concentrations whereas direct connections to nutrients are favoured when nutrient concentration is high. The results suggest that the foraging and minimising behaviour of Physarum-like transport networks reflect complex interplay between nutrient concentration, nutrient location, maximising foraging area coverage and minimising transport distance. The properties and behaviour of the synthetic virtual plasmodium may be useful in future physical instances of distributed unconventional computing devices, and may also provide clues to the generation of emergent computation behaviour by Physarum. © Springer Science+Business Media B.V. 2010.

• Journal Article Type: Article
• Publication Date: Dec 1, 2011
• Journal: Natural Computing
• Print ISSN: 1567-7818
• Electronic ISSN: 1572-9796
• Publisher: Springer (part of Springer Nature)
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 4
• Pages: 1345-1369
• DOI: https://doi.org/10.1007/s11047-010-9223-z
• Keywords: physarum polycephalum, transport networks, emergent behaviour, network minimisation, optimisation
• Public URL: https://uwe-repository.worktribe.com/output/985963
• Publisher URL: http://dx.doi.org/10.1007/s11047-010-9223-z