Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould

Abstract

Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould.

A Physarum-inspired approach to supply chain network design

“…Increasing the number of states in automaton could make model more realistic however fine-granular parallelism with a large number of node states leads to increased time consumption during modelling. The time consumption could be reduced when cellular automata models of Physarum are implemented in hardware [62][63][64]. We did not consider cellular automata as truly alternative models because they usually focus on the morphology of the patterns and their qualitative dynamics rather then quantitative transitions that are characteristic for supply chains.…”

A Cellular Automata Bioinspired Algorithm Designing Data Trees in Wireless Sensor Networks

“…The different modeling approaches have, also, various implementations, from the purely spatial CA models to mathematical representations of flux canalization, oscillatory behavior, two-variable Oregonator model of Belousov-Zhabotinsky (BZ) medium, and path length as found in literature [16][17][18][20][21][22][23][24][25][26][27].…”

Modified integral imaging reconstruction and encryption using an improved SR reconstruction algorithm

“…Recently, cellular automata (CA) based image encryption methods have been presented because of the capacity of parallel calculation and high security. CA are dynamical systems on finite state sets [33][34][35]. Pseudorandom number obtained by CA, which plays a very important role in image encryption.…”

“…">MonospectralEIs encrypted by linear CA and hyper-chaotic system 2.2.1. M-sequence generated by linear CA CA can offer significant benefit over existing algorithms [33,34]. In a one-dimensional (1D), two-state, three-site neighbourhood CA, where the next state of a cell is updated according to its neighborhood, the value of each cell is 0 or 1.…”