@inproceedings{c5c2b13efc2e44cbadf6d84fd95d05dd,
title = "Bee System with inhibition Pheromones",
abstract = "In previous work, we developed a foraging algorithm inspired by the behavior of biological bees. In relatively unobstructed environments, this algorithm has been shown to outperform an ant-inspired algorithm in terms of efficiency and scalability. However, due to its low adaptability outside of the hive, our bee-inspired algorithm displays weaker performance in more obstructed environments due to its nature to always use a straight, direct path to its destination without taking obstacles into account. In this paper, we present Bee System with inhibition Pheromones, a new, hybrid algorithm based on the recruitment and navigation strategies of bees and extended with inhibition pheromones to enhance adaptability. Moreover, wall following has been implemented to improve obstacle avoidance.We show that the hybrid algorithm truly combines the 'best of both worlds' and manages to outperform both our antinspired algorithm as our bee-inspired algorithm in a variety of experimental settings.",
keywords = "Multi-agent Systems, Swarm Intelligence, Bee Colony Optimization, Ant Colony Optimization",
author = "Nyree Lemmens and Karl Tuyls and Ann Nowe and \{De Jong\}, Steven",
year = "2007",
month = oct,
day = "1",
language = "English",
series = "European Conference on Complex Systems (ECCS)",
booktitle = "European Conference on Complex Systems (ECCS)",
}