Dancing for a decision: a matrix model for nest–site choice by honeybees

Myerscough, Mary R.

doi:10.1098/rspb.2002.2293

Cited by 34 publications

(20 citation statements)

References 20 publications

(36 reference statements)

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“…To understand how collective decision-making may be optimized in situations characterized by uncertainty, our models are stochastic differential equations, as in the neural case. This departs from previous modelling efforts using deterministic differential equations Pratt et al 2002), population matrix models (Myerscough 2003) or individual-based models (Pratt et al 2005;Marshall et al 2006). All the models represent flows between populations of individuals having different behavioural states.…”

Section: Models Of House -Hunting By Social Insect Coloniesmentioning

confidence: 99%

On optimal decision-making in brains and social insect colonies

Marshall

Bogacz²,

Dornhaus³

et al. 2009

J. R. Soc. Interface.

199

156

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The problem of how to compromise between speed and accuracy in decision-making faces organisms at many levels of biological complexity. Striking parallels are evident between decision-making in primate brains and collective decision-making in social insect colonies: in both systems, separate populations accumulate evidence for alternative choices; when one population reaches a threshold, a decision is made for the corresponding alternative, and this threshold may be varied to compromise between the speed and the accuracy of decisionmaking. In primate decision-making, simple models of these processes have been shown, under certain parametrizations, to implement the statistically optimal procedure that minimizes decision time for any given error rate. In this paper, we adapt these same analysis techniques and apply them to new models of collective decision-making in social insect colonies. We show that social insect colonies may also be able to achieve statistically optimal collective decision-making in a very similar way to primate brains, via direct competition between evidence-accumulating populations. This optimality result makes testable predictions for how collective decision-making in social insects should be organized. Our approach also represents the first attempt to identify a common theoretical framework for the study of decision-making in diverse biological systems.

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Section: Models Of House -Hunting By Social Insect Coloniesmentioning

confidence: 99%

On optimal decision-making in brains and social insect colonies

Marshall

Bogacz²,

Dornhaus³

et al. 2009

J. R. Soc. Interface.

199

156

View full text Add to dashboard Cite

show abstract

“…The standard problem examined in most modelling studies of the bees' decision-making process [15,22,28,29,[32][33][34][35][36][37][38] and in some controlled experimental studies (e.g. [6]) is to give swarms a choice between two to six nest sites (but see [39] for a modelling study with a choice between 120 distinct nest sites).…”

Section: Simulations-the Possible Effects Of Scout Numbers On Decisiomentioning

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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“…Other mathematical models of nest-site choice by honeybees are a differential equation model by Britton et al (2002), a matrix model by Myerscough (2003), another agent-based model by , and a density-dependent Markov process model by Perdriau & Myerscough (2007). While shedding light on several important aspects of the bees'decision process, none of these models exhibits both main characteristics of ours, i.e.…”

Section: Introductionmentioning

confidence: 99%

Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

List

Elsholtz

Seeley

2008

Phil. Trans. R. Soc. B

122

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Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees.

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Dancing for a decision: a matrix model for nest–site choice by honeybees

Abstract: A mathematical model is formulated for decision making by honeybees during nest-site choice, using a population matrix model. This model explains how the observed dynamics of the nest-site scouts' dancing can reliably lead to a choice of the best nest site available.

Cited by 34 publications

References 20 publications

On optimal decision-making in brains and social insect colonies

On optimal decision-making in brains and social insect colonies

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

Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

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