5 research outputs found
Exploiting Environmental Computation in a Multi-Agent Model of Slime Mould
Very simple organisms, such as the single-celled amoeboid slime mould
Physarum polycephalum possess no neural tissue yet, despite this, are known to
exhibit complex biological and computational behaviour. Given such limited
resources, can environmental stimuli play a role in generating the complexity
of slime mould behaviour? We use a multi-agent collective model of slime mould
to explore a two-way mechanism where the collective behaviour is influenced by
simulated chemical concentration gradient fields and, in turn, this behaviour
alters the spatial pattern of the concentration gradients. This simple
mechanism yields complex behaviour amid the dynamically changing gradient
profiles and suggests how the apparently intelligent response of the slime
mould could possibly be due to outsourcing of computation to the environment.Comment: 2014 ABBII International Symposium on Artificial, Biological and
Bio-Inspired Intelligence, 27-28th September, Rhodes, Greec
Applications to Biological Networks of Adaptive Hagen-Poiseuille Flow on Graphs
Physarum polycephalum is a single-celled, multi-nucleated slime mold whose
body constitutes a network of veins. As it explores its environment, it adapts
and optimizes its network to external stimuli. It has been shown to exhibit
complex behavior, like solving mazes, finding the shortest path, and creating
cost-efficient and robust networks. Several models have been developed to
attempt to mimic its network's adaptation in order to try to understand the
mechanisms behind its behavior as well as to be able to create efficient
networks. This thesis aims to study a recently developed, physically-consistent
model based on adaptive Hagen-Poiseuille flows on graphs, determining the
properties of the trees it creates and probing them to understand if they are
realistic and consistent with experiment. It also intends to use said model to
produce short and efficient networks, applying it to a real-life transport
network example. We have found that the model is able to create networks that
are consistent with biological networks: they follow Murray's law at steady
state, exhibit structures similar to Physarum's networks, and even present
peristalsis (oscillations of the vein radii) and shuttle streaming (the
back-and-forth movement of cytoplasm inside Physarum's veins) in some parts of
the networks. We have also used the model paired with different stochastic
algorithms to produce efficient, short, and cost-efficient networks; when
compared to a real transport network, mainland Portugal's railway system, all
algorithms proved to be more efficient and some proved to be more
cost-efficient.Comment: 106 pages, 59 figure