Bio-Inspired Transportation Network Optimisation Reinforcement Rules in Physarum Vein Networks

dc.contributor.authorDevers, Louis Etienne
dc.contributor.departmentChalmers tekniska högskola / Institutionen för fysik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Physics (Chalmers)en
dc.description.abstractThe decision making process of unicellular organisms such as the amoeba Physarum polycephalum may represent primitive forms of computation. Such non neuronal organisms exhibit complex optimisation behaviour, apparently solving NP hard problems in linear time. Understanding such behaviour may be relevant for many different fields besides biology, from metaheuristics to neuroscience or information theory. This master thesis explores possible reinforcement mechanisms Physarum polycephalum that influence vein network formation and biomass density distribution. The state-of-the-art Flow Conductivity Model (Tero et al 2006) that describes vein development will be tested for the first time experimentally using time-lapseimaging- techniques. If this model (also called the Physarum Solver) is the one used to reproduce the slime mold’s solving capacities it lacks many of the Physarum’s biological features, such as growth. However, we show that the Physarum expansion neglected by the Flow Conductivity Model was not necessary, as the order in which food sources were met did not influence the final distribution of biomass. By using fluorescence microscopy, we have been able to quantify the flow within the veins of the slime mold, extracting both the local diameter and the local flow rate within the veins. We notes that the contractile cycles missing from the model may have a strong impact on the decision making process. The fast contractile cycle creates the flow by dilating the vein and creating low-pressure points; while the phase of the slow contractile cycle distinguishes veins that will be reinforced from the other veins. The fit to the empirical data has a different form to the various model functions that have been used. However, even if the model does not fit experimental data trend, it still has utility for bio-inspired optimisation and pedagogical purposes. Furthermore, the Flow Conductivity Model may give us a better insight of the mechanic of the slime mold’s vein selection than a new model over-fitting experimental data.
dc.subjectPhysical Sciences
dc.titleBio-Inspired Transportation Network Optimisation Reinforcement Rules in Physarum Vein Networks
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
local.programmeComplex adaptive systems (MPCAS), MSc
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