The collective motion of animals in a group is a
fascinating topic of research for many scientists. Understanding these
collective behaviors can sometimes inspire the development of strategies for
promoting positive social change, as well as technologies that emulate nature.
Many studies describe flocking behavior as a
self-organized process, with individuals in a group continuously adapting their
direction and speed to ultimately achieve a "collective" motion. This
perspective, however, does not consider the hierarchical structure exhibited by
many animal groups and the possible benefits of having a "leader"
guide the way.
Luis Gómez-Nava, Richard Bon and Fernando Peruani,
three researchers at Université Côte d'Azur, Université de Toulouse, and CY
Cergy Paris Université have recently used physics theory to examine the
collective behavior of small flocks of sheep. Their findings, published in
Nature Physics, show that by alternating between the role of leader and
follower, the flock ultimately achieves some form of "collective
intelligence."
"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," Peruani told
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 key objective of the recent work by Peruani and
his colleagues was to investigate the collective motion of an animal system in
a way that explicitly considers the temporal aspect of the observed
self-organized process, specifically that collective motion phases have a
beginning and an end. In addition, the team wished to adopt an alternative and
holistic perspective, which considers the animal group's motion as a collection
of "collective phases."
"From this perspective, questions on the
mechanisms of information sharing and consensus decision-making adopt a new
dimension," Peruani explained.
In their experiment, Peruani and his colleagues
closely studied the spontaneous behavior of small groups of sheep over varying
time intervals. They analyzed the trajectories of individual flock members and
computed the animals' overall spatial order and orientation, while also
assessing correlations between the velocity at which individual animals moved.
"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."
Interestingly, Peruani and his colleagues found that
the interaction network representing the behavior of the flocks they observed
was highly hierarchical. In addition, they showed that the only information
propagated through this network is that related to the sheep's position within
the group.
Using their findings, the researchers built a model
of collective animal motion that focuses on two key cognitive processes. These
processes are the selection of a leader who will lead the flock for a specific
amount of time and the mechanism underlying the flock's navigation.
"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."
Essentially, the researchers' finding suggest that
while moving in flocks, sheep alternate between the role of leader and
follower. Leaders are thus only leading the group for a certain amount of time,
before control of the group is transferred to another sheep.
"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
said "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 gathered by Peruani and his colleagues
shed some new light on the dynamics underpinning the collective motion of small
sheep flocks. To investigate the extent to which these findings can be
generalized, however, further experiments with bigger herds and different
animals will need to be conducted.
"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."
Overall, the recent work by this team of researchers
highlights the possibility that some naturally occurring collective animal
strategies take advantage of both hierarchical and democratic organizational
schemes. In the future, their observations could inspire new studies
investigating the physics and biology underpinning these intriguing collective
animal behaviors.
"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. "
Reference: Nature Physics
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