Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould

Area of Science:

• Computational intelligence
• Bio-inspired computing
• Network design

Background:

• The shortest path problem is central to transport network design and computational intelligence.
• Biological computing substrates, like Physarum polycephalum (P. polycephalum), offer unique approaches but are slow.
• Mapping slime mould computing mechanisms to silicon can yield efficient bio-inspired devices.

Purpose of the Study:

• To propose a cellular automaton (CA)-based model inspired by P. polycephalum for designing network structures.
• To emulate the slime mould's propagating strategy, tubular network formation, and computational abilities.
• To provide a virtual emulator for network design, reducing experimental time and cost.

Main Methods:

• Development of a novel cellular automaton (CA) model.
• Inspiration drawn from the slime mould Physarum polycephalum's biological strategies.
• Validation against experimental results of slime mould-based network imitation.

Main Results:

• The CA model successfully mimics the formation of tubular networks.
• Results align well with previous laboratory studies using P. polycephalum.
• The model demonstrates a good match with experimental imitation of transport networks.

Conclusions:

• The proposed CA model serves as an effective virtual emulator for studying network design.
• It significantly economizes the time required for biological experiments.
• The model produces networks comparable to those formed by the real slime mould, Physarum polycephalum.