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Bee behaviour in multi-agent systems: a bee foraging algorithm Host Publication: Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning Authors: N. Lemmens, K. Tuyls, A. Nowé and S. De Jong Publisher: Springer Publication Date: Feb. 2008 ISBN: 978-3-540-77947-6
Abstract: In this paper we present a new, non-pheromone-based algorithm inspired by the behaviour of bees. The algorithm combines both recruitment and navigation strategies. We investigate whether this new algorithm outperforms pheromone-based algorithms, inspired by the behaviour of ants, in the task of foraging. From our experiments, we conclude that (i) the bee-inspired algorithm is significantly more efficient when finding and collecting food, i.e., it uses fewer iterations to complete the task (ii) the bee-inspired algorithm is more scalable, i.e., it requires less computation time to complete the task, even though in small worlds, the ant-inspired algorithm is faster on a time-per-iteration measure and finally, (iii) our current bee-inspired algorithm is less adaptive than ant-inspired algorithms. External Link.
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