Honeybee swarms: how do scouts guide a swarm of uninformed bees?

Janson, Stefan; Middendorf, Martin; Beekman, Madeleine

doi:10.1016/j.anbehav.2004.10.018

Cited by 94 publications

(79 citation statements)

References 18 publications

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“…The phenomena of formation acquisition and maintenance can be observed in nature in many forms, e.g., flocking birds, schooling fish, and swarming bees (see e.g. Hubbard, Babak, Sigurdsson, & Magnusson, 2004;Janson, Middendorf, & Beekman, 2005). Motivated by these observations, a significant number of recent studies have been performed in engineering applications including UAVs, roving robots, collection of ships, submarines, etc (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Three and higher dimensional autonomous formations: Rigidity, persistence and structural persistence

et al. 2007

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In this paper, we generalize the notion of persistence, which has been originally introduced for two-dimensional formations, to R d for d 3, seeking to provide a theoretical framework for real world applications, which often are in three-dimensional space as opposed to the plane. Persistence captures the desirable property that a formation moves as a cohesive whole when certain agents maintain their distances from certain other agents. We verify that many of the properties of rigid and/or persistent formations established in R 2 are also valid for higher dimensions. Analysing the closed subgraphs and directed paths in persistent graphs, we derive some further properties of persistent formations. We also provide an easily checkable necessary condition for persistence. We then turn our attention to consider some practical issues raised in multi-agent formation control in three-dimensional space. We display a new phenomenon, not present in R 2 , whereby subsets of agents can behave in a problematic way. When this behaviour is precluded, we say that the graph depicting the multi-agent formation has structural persistence. In real deployment of controlled multi-agent systems, formations with underlying structurally persistent graphs are of interest. We analyse the characteristics of structurally persistent graphs and provide a streamlined test for structural persistence. We study the connections between the allocation of degrees of freedom (DOFs) across agents and the characteristics of persistence and/or structural persistence of a directed graph. We also show how to transfer DOFs among agents, when the formation changes with new agent(s) added, to preserve persistence and/or structural persistence. ᭧

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Section: Introductionmentioning

confidence: 99%

Three and higher dimensional autonomous formations: Rigidity, persistence and structural persistence

et al. 2007

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“…Bees that experience the quorum return to the swarm and attempt to rouse the rest of the swarm to prepare for flight by producing high-pitched, auditory, piping signals and jostling their way across the swarm performing vigorous buzz runs. Over time the tightly clustered swarm loosens and eventually takes flight; bees that know the location of the new nest site guide the rest of the swarm to their new home by a process of streaking (flying at high speed through the swarm in the direction of the new nest site) [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Do small swarms have an advantage when house hunting? The effect of swarm size on nest-site selection by Apis mellifera

Schaerf

Makinson

Myerscough

et al. 2013

J. R. Soc. Interface.

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Reproductive swarms of honeybees are faced with the problem of finding a good site to establish a new colony. We examined the potential effects of swarm size on the quality of nest-site choice through a combination of modelling and field experiments. We used an individual-based model to examine the effects of swarm size on decision accuracy under the assumption that the number of bees actively involved in the decision-making process (scouts) is an increasing function of swarm size. We found that the ability of a swarm to choose the best of two nest sites decreases as swarm size increases when there is some time-lag between discovering the sites, consistent with Janson & Beekman (Janson & Beekman 2007 Proceedings of European Conference on Complex Systems, pp. 204-211.). However, when simulated swarms were faced with a realistic problem of choosing between many nest sites discoverable at all times, larger swarms were more accurate in their decisions than smaller swarms owing to their ability to discover nest sites more rapidly. Our experimental fieldwork showed that large swarms invest a larger number of scouts into the decision-making process than smaller swarms. Preliminary analysis of waggle dances from experimental swarms also suggested that large swarms could indeed discover and advertise nest sites at a faster rate than small swarms.

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“…As shown in Figure 6, a few informed individuals (or pseudo-leaders) of a fish school or a bee swarm can guide the whole group towards the target (or help the group follow the trajectory of the leader) [24], [25], [36]. The role of pseudo-leaders has also been investigated by Couzin [35], who showed that the larger the group the smaller the proportion of informed individuals needed to guide the group, and that only a very small proportion of informed individuals is required to achieve remarkable accuracy.…”

Section: A Predictive Mechanisms For Flocks Governed By A/r Modelmentioning

confidence: 99%