Trans-Canada Slimeways

2014 ◽  
pp. 251-265
Author(s):  
Andrew Adamatzky ◽  
Selim G. Akl
Keyword(s):  
Urban Areas ◽  
Physarum Polycephalum ◽  
Minimum Energy ◽  
Extended Body ◽  
Slime Mould ◽  
Proximity Graphs ◽  
Maximum Coverage ◽  
National Highway ◽  
Highway Network ◽  
Similarities And Differences

Slime mould Physarum polycephalum builds up sophisticated networks to transport nutrients between distant parts of its extended body. The slime mould’s protoplasmic network is optimised for maximum coverage of nutrients yet minimum energy spent on transportation of the intra-cellular material. In laboratory experiments with P. polycephalum we represent Canadian major urban areas with rolled oats and inoculated slime mould in the Toronto area. The plasmodium spans the urban areas with its network of protoplasmic tubes. The authors uncover similarities and differences between the protoplasmic network and the Canadian national highway network, analyse the networks in terms of proximity graphs and evaluate slime mould’s network response to contamination.

Trans-Canada Slimeways

2011 ◽  
Vol 2 (4) ◽  
pp. 31-46 ◽  
Author(s):  
Andrew Adamatzky ◽  
Selim G. Akl
Keyword(s):  
Urban Areas ◽  
Physarum Polycephalum ◽  
Laboratory Experiments ◽  
Minimum Energy ◽  
Extended Body ◽  
Slime Mould ◽  
Proximity Graphs ◽  
Maximum Coverage ◽  
Highway Network ◽  
Similarities And Differences

Slime mould Physarum polycephalum builds up sophisticated networks to transport nutrients between distant parts of its extended body. The slime mould’s protoplasmic network is optimised for maximum coverage of nutrients yet minimum energy spent on transportation of the intra-cellular material. In laboratory experiments with P. polycephalum we represent Canadian major urban areas with rolled oats and inoculated slime mould in the Toronto area. The plasmodium spans the urban areas with its network of protoplasmic tubes. The authors uncover similarities and differences between the protoplasmic network and the Canadian national highway network, analyse the networks in terms of proximity graphs and evaluate slime mould’s network response to contamination.

Physarum Itinerae

2011 ◽  
Vol 3 (2) ◽  
pp. 31-55 ◽  
Author(s):  
Emanuele Strano ◽  
Andrew Adamatzky ◽  
Jeff Jones
Keyword(s):  
Roman Empire ◽  
Iron Age ◽  
Physarum Polycephalum ◽  
Minimum Spanning Tree ◽  
Transport Systems ◽  
Test Bed ◽  
Slime Mould ◽  
Proximity Graphs ◽  
Road Development ◽  
Experimental Laboratory

The Roman Empire is renowned for sharp logical design and outstanding building quality of its road system. Many roads built by Romans are still used in continental Europe and UK. The Roman roads were built for military transportations with efficiency in mind, as straight as possible. Thus the roads make an ideal test-bed for developing experimental laboratory techniques for evaluating man-made transport systems using living creatures. The authors imitate development of road networks in Iron Age Italy using slime mould Physarum polycephalum. The authors represent ten Roman cities with oat flakes, inoculate the slime mould in Roma, wait as mould spans all flakes-cities with its network of protoplasmic tubes, and analyse structures of the protoplasmic networks. The authors found that most Roman roads, a part of those linking Placentia to Bononia and Genua to Florenzia are represented in development of Physarum polycephalum. Transport networks developed by Romans and by slime mould show similarities of planar proximity graphs, and particular minimum spanning tree. Based on laboratory experiments the authors reconstructed a speculative sequence of road development in Iron Age Italy.

scholarly journals BIO-DEVELOPMENT OF MOTORWAY NETWORK IN THE NETHERLANDS: A SLIME MOULD APPROACH

2013 ◽  
Vol 16 (02n03) ◽  
pp. 1250034 ◽  
Author(s):  
ANDREW ADAMATZKY ◽  
MICHAEL LEES ◽  
PETER SLOOT
Keyword(s):  
The Netherlands ◽  
Physarum Polycephalum ◽  
Transport Networks ◽  
Slime Mould ◽  
Proximity Graphs ◽  
Upper Limits ◽  
Cellular Slime ◽  
Motorway Networks ◽  
Eukaryotic Microbe

Plasmodium of a cellular slime mould Physarum polycephalum is a very large eukaryotic microbe visible to the unaided eye. During its foraging behavior the plasmodium spans sources of nutrients with a network of protoplasmic tubes. In this paper we attempt to address the following question: Is slime mould capable of computing transport networks? By assuming the sources of nutrients are cities and protoplasmic tubes connecting the sources are motorways, how well does the plasmodium approximate existing motorway networks? We take the Netherlands as a case study for bio-development of motorways, while it has the most dense motorway network in Europe, current demand is rapidly approaching the upper limits of existing capacity. We represent twenty major cities with oat flakes, place plasmodium in Amsterdam and record how the plasmodium spreads between oat flakes via the protoplasmic tubes. First we analyze slime-mould-built and man-built transport networks in a framework of proximity graphs to investigate if the slime mould is capable of computing existing networks. We then go on to investigate if the slime mould is able calculate or adapt the network through imitating restructuring of the transport network as a response to potential localized flooding of the Netherlands.

DEVELOPING PROXIMITY GRAPHS BY PHYSARUM POLYCEPHALUM: DOES THE PLASMODIUM FOLLOW THE TOUSSAINT HIERARCHY?

2009 ◽  
Vol 19 (01) ◽  
pp. 105-127 ◽  
Author(s):  
ANDREW ADAMATZKY
Keyword(s):  
Foraging Behavior ◽  
Delaunay Triangulation ◽  
Spanning Tree ◽  
Physarum Polycephalum ◽  
Minimum Spanning Tree ◽  
Nearest Neighbour ◽  
Minimal Spanning Tree ◽  
Proximity Graphs ◽  
Relative Neighborhood Graph ◽  
Plasmodium Of Physarum Polycephalum

Plasmodium of Physarum polycephalum spans sources of nutrients and constructs varieties of protoplasmic networks during its foraging behavior. When the plasmodium is placed on a substrate populated with sources of nutrients, it spans the sources with protoplasmic network. The plasmodium optimizes the network to deliver efficiently the nutrients to all parts of its body. How exactly does the protoplasmic network unfold during the plasmodium's foraging behavior? What types of proximity graphs are approximated by the network? Does the plasmodium construct a minimal spanning tree first and then add additional protoplasmic veins to increase reliability and through-capacity of the network? We analyze a possibility that the plasmodium constructs a series of proximity graphs: nearest-neighbour graph (NNG), minimum spanning tree (MST), relative neighborhood graph (RNG), Gabriel graph (GG) and Delaunay triangulation (DT). The graphs can be arranged in the inclusion hierarchy (Toussaint hierarchy): NNG ⊆ MST ⊆ RNG ⊆ GG ⊆ DT . We aim to verify if graphs, where nodes are sources of nutrients and edges are protoplasmic tubes, appear in the development of the plasmodium in the order NNG → MST → RNG → GG → DT , corresponding to inclusion of the proximity graphs.

scholarly journals Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks

2015 ◽  
Vol 25 (01) ◽  
pp. 1540004 ◽  
Author(s):  
Jeff Jones
Keyword(s):  
Physarum Polycephalum ◽  
Network Formation ◽  
Proximity Graphs ◽  
Complex Adaptive ◽  
Division Problems ◽  
Scaling Parameters ◽  
Angle Rotation ◽  
Multi Agent ◽  
Robotic Devices ◽  
Adaptive Behaviours

The giant amoeboid organism true slime mould Physarum polycephalum dynamically adapts its body plan in response to changing environmental conditions and its protoplasmic transport network is used to distribute nutrients within the organism. These networks are efficient in terms of network length and network resilience and are parallel approximations of a range of proximity graphs and plane division problems. The complex parallel distributed computation exhibited by this simple organism has since served as an inspiration for intensive research into distributed computing and robotics within the last decade. P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this ‘computer’ be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus location, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms induce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, movement, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for complex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.

Lessons from a virtual slime: marginal mechanisms, minimal cognition and radical enactivism

2019 ◽  
Vol 28 (6) ◽  
pp. 453-464
Author(s):  
Lachlan Douglas Walmsley
Keyword(s):  
Physarum Polycephalum ◽  
Agent Model ◽  
Radical Enactivism ◽  
Slime Mould ◽  
Multi Agent ◽  
The Mind

Radical enactivism (REC) and similar embodied and enactive approaches to the mind deny that cognition is fundamentally representational, skull-bound and mechanistic in its organisation. In this article, I argue that modellers may still adopt a mechanistic strategy to produce explanations that are compatible with REC. This argument is scaffolded by a multi-agent model of the true slime mould Physarum polycephalum.

scholarly journals Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4682 ◽  
Author(s):  
Grzegorz Sierpiński ◽  
Marcin Staniek ◽  
Marcin Jacek Kłos
Keyword(s):  
Decision Making ◽  
Electric Vehicles ◽  
Urban Areas ◽  
Minimum Energy ◽  
Initial State ◽  
Local Authorities ◽  
Additional Energy ◽  
Charging Station ◽  
Charging Stations ◽  
Decision Making Support

Development of electromobility in urban areas requires an appropriate level of vehicle charging infrastructure. Numerous methods for siting of charging stations have been developed to date, and they appear to be delivering diverse outcomes for the same area, which is why local authorities face the problem of choosing the right station layout. The solution proposed in this article is to use a travel planner to evaluate the distribution of charging stations over the area of a metropolis. The decision making support is achieved by determining optimal travel routes for electric vehicles according to their initial state of charge for the three selected station siting methods. The evaluation focused on the following three aspects: (1) number of travels that cannot be made (due to the lack of a charging station at a certain distance around the start point), (2) extension of the travel caused by the need to recharge the vehicle on-route, and (3) additional energy consumption by electric vehicles required to reach the charging station (necessity of departing from the optimal route). An analysis of the results has made it possible to determine a solution which is superior to others. For the case study analysed in the paper, i.e., the territory of the Metropolis of Upper Silesia and Dabrową Basin (Górnośląsko-Zagłębiowska Metropolia, GZM), the distribution of charging stations established in line with method I has returned the best results. What the method in question also makes possible is to indicate a safe minimum energy reserve to complete the travel by eliminating situations of unexpected vehicle immobilisation due to on-route energy depletion and by minimising the phenomenon referred to as range anxiety.

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