Previous work has shown that virtual hormone systems can be engineered to arbitrate swarms of robots between sets of behaviours. These virtual hormones act similarly to their natural counterparts, providing a method of online, reactive adaptation. It is yet to be shown how virtual hormone systems could be used when a robotic swarm has a large variety of task types to execute. This paper details work that demonstrates the viability of a collection of virtual hormones that can be used to regulate and adapt a swarm over time, in response to different environments and tasks. Specifically, the paper examines a new method of hormone speed control for energy efficiency and combines it with two existing systems controlling environmental preference as well as a selection of behaviours that produce an effective foraging swarm. Experiments confirm the effectiveness of the combined system, showing that a swarm of robots equipped with multiple virtual hormones can forage efficiently to a specified item demand within an allotted period of time.
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Wilson et al. (2019) studied this question.
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