Abstract
We investigate an artificial self-organizing multi-particle (also multi-agent or swarm) system consisting of many (up to 103) reactive, mobile agents. The agents’ movements are governed by a few simple rules and interact indirectly via a pheromone field. The system generates a wide variety of complex patterns. For some parameter settings this system shows a notable property: seemingly never-ending, dynamic formation and reconfiguration of complex patterns. For other settings, however, the system degenerates and converges after a transient to patterns of low complexity. Therefore, we consider this model as an example of a class of self-organizing systems that show complex behavior mainly in the transient. In a first case study, we inspect the possibility of using a standard genetic algorithm to prolongate the transients. We present first promising results and investigate the evolved system.
Supported by: EU-IST-FET project ‘SYMBRION’, no. 216342; EU-ICT project ‘REPLICATOR’, no. 216240.
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Hamann, H., Schmickl, T., Crailsheim, K. (2011). Evolving for Creativity: Maximizing Complexity in a Self-organized Multi-particle System. In: Kampis, G., Karsai, I., Szathmáry, E. (eds) Advances in Artificial Life. Darwin Meets von Neumann. ECAL 2009. Lecture Notes in Computer Science(), vol 5777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21283-3_55
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DOI: https://doi.org/10.1007/978-3-642-21283-3_55
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