Variability and Heterogeneity in Natural Swarms: Experiments and Modeling

Ariel, Gil; Ayali, Amir; Be’er, Avraham; Knebel, Daniel

doi:10.1007/978-3-030-93302-9_1

Cited by 4 publications

(5 citation statements)

References 164 publications

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“…Bodily states, such as hunger or energy levels, as well as specieswide perceptual and cognitive capacity (such as the geometry of the visual field or motion prediction capabilities) are also ignored. Moreover, as a result of abstracting the embodied characteristics, individual variances within the swarm are generally also disregarded (Ariel et al, 2022).…”

Section: Empirical Studies Of Collective Motionmentioning

confidence: 99%

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective

Ayali

Kaminka

2023

Front. Neurorobot.

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Swarming or collective motion is ubiquitous in natural systems, and instrumental in many technological applications. Accordingly, research interest in this phenomenon is crossing discipline boundaries. A common major question is that of the intricate interactions between the individual, the group, and the environment. There are, however, major gaps in our understanding of swarming systems, very often due to the theoretical difficulty of relating embodied properties to the physical agents—individual animals or robots. Recently, there has been much progress in exploiting the complementary nature of the two disciplines: biology and robotics. This, unfortunately, is still uncommon in swarm research. Specifically, there are very few examples of joint research programs that investigate multiple biological and synthetic agents concomitantly. Here we present a novel research tool, enabling a unique, tightly integrated, bio-inspired, and robot-assisted study of major questions in swarm collective motion. Utilizing a quintessential model of collective behavior—locust nymphs and our recently developed Nymbots (locust-inspired robots)—we focus on fundamental questions and gaps in the scientific understanding of swarms, providing novel interdisciplinary insights and sharing ideas disciplines. The Nymbot-Locust bio-hybrid swarm enables the investigation of biology hypotheses that would be otherwise difficult, or even impossible to test, and to discover technological insights that might otherwise remain hidden from view.

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Section: Empirical Studies Of Collective Motionmentioning

confidence: 99%

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective

Ayali

Kaminka

2023

Front. Neurorobot.

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“…Collective behaviour can be defined as emergent and self-organising macroscopic collective motion and pattern formation arising from simple inter-individual and environmental interactions [6, 48, 49]. Due to the simple nature of these interactions, mathematical models have proven to be an important tool in studying this phenomenon [4]. These mathematical models can be broadly classified as either discrete, where organisms are modelled as individuals or continuum in which they are represented as a continuous density function [4].…”

Section: Introductionmentioning

confidence: 99%

“…Due to the simple nature of these interactions, mathematical models have proven to be an important tool in studying this phenomenon [4]. These mathematical models can be broadly classified as either discrete, where organisms are modelled as individuals or continuum in which they are represented as a continuous density function [4].…”

Section: Introductionmentioning

confidence: 99%

“…For example, hungrier individuals tend to migrate towards the front of moving groups in both caterpillars [30] and crimson spotted rainbow-fish [25], while faster pigeons hold a leadership position in flocks [35]. Whilst numerous examples of modelling heterogeneity exist, they are however dominated by SPP models [4], with very few examples of continuous ones [32], and to our knowledge none that include both phenotypic and environmental heterogeneity. In this paper, we derive a kinematic model for collective behaviour which considers both phenotypic heterogeneity (in the form of an internal state) and environmental interactions.…”

Section: Introductionmentioning

confidence: 99%

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Including organism and environmental heterogeneity in kinematic continuum models of collective behaviour with applications to locust foraging and group structure

Georgiou,

Buhl,

Green

et al. 2023

Preprint

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Collective behaviour occurs at all levels of the natural world, from cells joining together to form complex structures, to locusts interacting to form large and destructive plagues. These complex behaviours arise from simple individual and environmental interactions, and thus lend themselves well to mathematical modelling. One simplifying assumption, that of relative homogeneity of organisms, is often applied to keep the mathematics tractable. However, heterogeneity arising due to the internal state of individuals has an impact on these interactions and thus plays a role in group structure and dynamics.In this paper, we introduce a continuum model that accounts for this heterogeneity in the form of a state space that models an organisms internal state and converts this to movement characteristics. Using a variety analytic techniques, we investigate the effect of internal state on aggregation density and aggregation formation behaviour, finding that density and formation is most affected by the ratio of attractive to dispersive interactions.We then apply the model to a concrete example of locust foraging to investigate the effect of food, hunger, and gregarisation on locust group formation and structure. Through numerical simulations we find that the most gregarious and satiated locusts tend to be located towards the centre of locust groups. Conversely, hunger drives locusts towards the edges of the group. Finally, we find that locust group dispersal may be driven in part by hunger.Author SummaryCollective behaviour occurs at all levels of the natural world, from cells joining together to form complex structures, to locusts interacting to form large and destructive plagues. We can modelling these complex behaviours using mathematical models however we often need to rely on simplifying assumptions to keep the mathematics easy enough to analyse. One simplifying assumption that is often employed is assuming that all the modelled organisms are the same (or in one of only a few possible states). However, this is often not the case in nature where the differences between individuals arising due to internal characteristics, such as hunger or age, often affects their behaviour and thus can change group dynamics.In this paper we introduce a mathematical model that is able to capture these differences and apply the newly developed model to locust foraging. We find that hunger tends to drive individuals to the edges of aggregations as well as lowers the maximum possible density. These two results combine to give a possible mechanism for the dispersal of locust groups.

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“…In nature, bacteria grow in a variety of habitats. In most cases, several species, or variants of the same species, occupy the same niche, creating a heterogeneous population with a diverse range of interactions between them (e.g., 3 , 4 ). It has been suggested that population heterogeneity could enable bacteria to better exploit the local environment as well as to optimize exploration of new territories 5 , 6 .…”

Section: Introductionmentioning

confidence: 99%

Mixed-species bacterial swarms show an interplay of mixing and segregation across scales

Natan

Worlitzer²,

Ariel³

et al. 2022

Sci Rep

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Bacterial swarms are a highly-researched example of natural active matter. In particular, the interplay between biological interactions and the physics underlying the swarming dynamics is of both biological and physical interest. In this paper, we study mixed swarms of Bacillus subtilis and Pseudomonas aeruginosa. We find intricate interactions between the species, showing both cooperation and segregation across different spatial and temporal scales. On one hand, even though axenic colonies grow on disparate time scale, an order of magnitude apart, the two-species swarm together, forming a single, combined colony. However, the rapidly moving populations are locally segregated, with different characteristic speeds and lengths (or cluster sizes) that depend on the ratio between the species. Comparison with controlled mutant strains suggest that both the physical and known biological differences in species characteristics may not be enough to explain the segregation between the species in the mixed swarm. We hypothesize that the heterogeneous spatial distribution is due to some mechanism that enables bacteria to recognize their own kind, whose precise origin we could not identify.

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Variability and Heterogeneity in Natural Swarms: Experiments and Modeling

Cited by 4 publications

References 164 publications

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective

Including organism and environmental heterogeneity in kinematic continuum models of collective behaviour with applications to locust foraging and group structure

Mixed-species bacterial swarms show an interplay of mixing and segregation across scales

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