Abstract
Having simple agents capable of cooperatively distinguishing one shape from another is an interesting problem, which will have benefits in the future. An abstracted model of this was tested with neighbouring agents who change state according to their immediate surroundings, changing the surroundings themselves. Using a genetic algorithm to determine the agent behaviours at each state it was possible to train a swarm to remove only one out of two unknown types of shape in an enclosed space. Estimates of the difficulty the genetic algorithm would have in finding a suitable solution had a significant correlation with the measured difficulty in the eleven tested scenarios, with known solutions.
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King, D., Breedon, P. (2014). Cooperative Object Recognition: Behaviours of a Artificially Evolved Swarm. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2014. Lecture Notes in Computer Science, vol 8667. Springer, Cham. https://doi.org/10.1007/978-3-319-09952-1_19
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DOI: https://doi.org/10.1007/978-3-319-09952-1_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09951-4
Online ISBN: 978-3-319-09952-1
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