Intelligent Control of Transportation Flow in Physarum Networks
Bingyang Han, Luolan Chen, Tieyan Si

TL;DR
This paper explores how Physarum networks exhibit intelligent, adaptive flow control mechanisms that prevent congestion, with potential applications in traffic management and insights into physical models like spin ice.
Contribution
It uncovers the physical principles behind Physarum's adaptive flow regulation, linking biological flow dynamics to statistical physics models and traffic congestion prevention.
Findings
Flow fluxes obey Kirchhoff's law at intersections
Flow vectors follow the ice-rule in spin ice models
Y-shaped nodes avoid simultaneous blockage
Abstract
The Physarum network expands or retracts in response to environmental stimuli, demonstrating an intelligent adaptive capability to locate optimal paths for nutrient transport. The underlying physical mechanism governing this intelligence behavior remains an unresolved problem in biological physics.unlike the unidirectional flow typical of urban traffic networks, cytoplasmic flow within the Physarum network exhibits periodic oscillations modulated by biological repellents and attractants. In this study, we investigate how local flows within the networks branch channels interact to collectively govern the global oscillatory dynamics.We find that the measured flow fluxes at intersection nodes obey Kirchhoff's current law. Phase differences exist among the flows in different branches.At the microscopic scale, flow distribution exhibits only brief periods of traffic congestion, which are…
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Taxonomy
TopicsSlime Mold and Myxomycetes Research · Plant and Biological Electrophysiology Studies · Neural Networks and Reservoir Computing
