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Sheep flocks operate as a type of 'collective intelligence' and elect temporary leaders to guide them while moving

The fluidity of this process is extremely surprising.

Alexandru Micu
November 18, 2022 @ 8:22 pm

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Sheep flocks follow surprisingly dynamic structures, new research reports, as individual sheep alternate between the role of leader and follower to produce a form of “collective intelligence”.

Image credits Pixabay.

Some animals out there really do surprise us with their smarts. Sheep, in general, are not one of those animals for most people. But whatever these wooly critters may lack in apparent individual intelligence, they make up for in groups, new research shows. According to the findings, the collective behavior of sheep in a flock follows a self-organizing principle, with individuals continuously adapting their direction and speed in such a way as to give rise to a “collective” motion.

The animals alternate between leading the flock and following another leader, the authors explain, in an organic and highly fluid manner. Such processes represent an example of collective intelligence that can teach us more about how self-organizing systems can share information among their individual parts, giving us insight into how to recreate such systems in the future.

Sheep leads the way

“In most gregarious animal systems, collective motion is not a continuous process, but occurs in episodes: collective motion phases are interrupted, for instance, to rest or feed,” said Fernando Peruani, corresponding author of the paper, for Phys.org. “Nevertheless, most collective motion studies, including experimental and theoretical ones, consider groups that remain, from the beginning till the end, on the move. Furthermore, it is often assumed that flocking behavior requires individuals to continuously negotiate on the direction of travel.”

The research trio behind this paper, from Université Côte d’Azur, Université de Toulouse, and CY Cergy Paris Université, employed physics theories to study the collective behavior of small flocks of sheep. Their main objective was to investigate these systems from the point of view of finite, self-organizing collective motions. Such an approach, they explain, allowed them to better probe into the decision-making processes of individual sheep to understand how the motions of the overall flock arise.

For the experiment, the team studied the natural behavior of small groups of sheep over different time intervals. The movement trajectories of each individual sheep was tracked, as well as their orientation and position in the flock.

“We first showed that none of the existing flocking models, or extensions of them, is consistent with our observations,” Peruani said. “Then, we analyzed how information travels through the group, identifying an interaction network consistent with the data, and investigated which information is transmitted through this network.”

All in all, the team concluded that the interactions seen between individual flock members were highly hierarchical. Furthermore, all the animals in the herd form a network, and information is distributed throughout this network according to each animal’s position in the group.

Based on their observations, the team built a model of collective animal motion that focuses on two cognitive processes: leader selection, with each leader guiding the flock for a specific amount of time, and a navigation mechanism, which underpins where the flock goes.

“Importantly, each collective motion phase possesses a temporal leader,” Peruani explained, “We investigated the mathematical properties of the resulting model to identify the advantages of the unveiled collective strategy. I believe that the main contribution is the following: the animals, by using a hierarchical interaction network to move together for a while give full control of the group to the temporal leader, but there is also a rapid turnover of temporal leaders.”

“If a temporal leader has knowledge relevant to the group (e.g., the way out of a maze or the location of a food source) then, the temporal leader will be able to efficiently guide the group,” Peruani adds. “In this way, all group members take advantage of that knowledge. It is worth noting that this only works if all individuals follow the temporal leader without questioning.”

The findings essentially suggest that the flock doesn’t have a definite leader, but different animals take turns in this role. What is particularly interesting here is how fluid this transition is: in human societies, the transfer of authority or leadership is often marked by uncertainty and chaos.

What we don’t yet know, however, is how the flock decides that it is time for a new leader to take the reins, or how that leader is determined. Further experiments will be needed to determine this, as well as to help us understand whether such dynamics apply to other herd animals as well, or are limited only to sheep.

“We wondered: if there is a temporal leader at every moment, how does the group share and process information that each individual member of the group may have? Can the group perform information pooling to improve its ability to accurately navigate to a distant place? In short, does the group exhibit collective intelligence?” Peruani said. “We proved that by regularly changing the temporal leader, the group is able to exhibit information pooling and collective intelligence.”

The findings are of interest especially for researchers working with informational systems, or swarm-like applications, such as cooperative robots. Sheep flocks merge aspects from both hierarchical and democratic structures, with one leader having complete control over where the flock goes, but the flock retaining full control of who that leader is at any point in time.

“We are now investigating collective motion using groups of different agents,” Peruani added. “Specifically, we are comparing the spontaneous behavior of groups of lambs, young sheep, and adult sheep, to investigate whether sheep learn to follow temporal leaders and to act as one over time. We are also investigating how groups behave in complex environments such as mazes or arenas with different food patches that can trigger a conflict of interests within group members. And more generally, we are investigating how collectives distribute and process information, using several statistical mechanics tools.”

The paper “Intermittent collective motion in sheep results from alternating the role of leader and follower” has been published in the journal Nature Physics.

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