Bee behaviour in multi-agent systems: a bee foraging algorithm

Authors:
Nyree Lemmens;Steven De Jong;Karl Tuyls;Ann Nowé
Affiliations:
CoMo, Vrije Universiteit Brussel, Belgium;MICC-IKAT, Universiteit Maastricht, Netherlands;MICC-IKAT, Universiteit Maastricht, Netherlands;CoMo, Vrije Universiteit Brussel, Belgium
Venue:
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Year:
2005

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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.