Abstract
At first glance the activities of insects do not appear to be an obvious source of inspiration for natural computing algorithms. However, on closer inspection it becomes apparent that many insects are capable of exceedingly complex behaviours. They can process a multitude of sensory inputs, modulate their behaviour according to these stimuli, and make decisions on the basis of a large amount of environmental information. Yet the complexity of individual insects is not sufficient to explain the complexity that many societies of insects can achieve [68]. Although only 2% of all insect species are social, these species have been remarkably successful at earning a living in their environment and comprise more than 50% of the global total insect biomass [19]. This suggests that the social nature of these species could be contributing to their relative success in colonising the natural world.
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© 2015 Springer-Verlag Berlin Heidelberg
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Brabazon, A., O’Neill, M., McGarraghy, S. (2015). Ant Algorithms. In: Natural Computing Algorithms. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43631-8_9
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DOI: https://doi.org/10.1007/978-3-662-43631-8_9
Publisher Name: Springer, Berlin, Heidelberg
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