ABSTRACT
Inspired by the chemotaxis interaction of living cells, we have developed an agent-based approach for self-organising shape formation. Since all our simulations begin with a different uniform random configuration and our agents move stochastically, it has been observed that the self-organisation process may form two or more stable final configurations. These differing configurations may be characterised via statistical moments of the agents' locations. In order to direct the agents to robustly form one specific configuration, we generate biased initial conditions whose statistical moments are related to moments of the desired configuration. With this approach, we are able to successfully direct the aggregating swarms to produce a desired macroscopic shape, starting from randomised initial conditions with controlled statistical properties.
Acknowledgments
The authors would like to thank Robert Gilmore, Christian Kuehn, and Santiago Ontañón for many helpful discussions and suggestions.
Disclosure statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.