Evolving for Creativity: Maximizing Complexity in a Self-organized Multi-particle System View Full Text


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Chapter Info

DATE

2011

AUTHORS

Heiko Hamann , Thomas Schmickl , Karl Crailsheim

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. More... »

PAGES

442-449

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-21283-3_55

DOI

http://dx.doi.org/10.1007/978-3-642-21283-3_55

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044369657


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