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Swarm behaviour, or swarming, is a collective behaviour exhibited by entities, particularly animals, of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or animal migration in some direction. It is a highly interdisciplinary topic. (2025). 9789812877505, Springer. ISBN 9789812877505
As a term, swarming is applied particularly to insects, but can also be applied to any other entity or animal that exhibits swarm behaviour. The term flocking or murmuration can refer specifically to swarm behaviour in birds, herd behaviour to refer to swarm behaviour in tetrapods, and shoaling or schooling to refer to swarm behaviour in fish. Phytoplankton also gather in huge swarms called algal bloom, although these organisms are algae and are not self-propelled the way most animals are. By extension, the term "swarm" is applied also to inanimate entities which exhibit parallel behaviours, as in a swarm robotics, an earthquake swarm, or a swarm of stars.
From a more abstract point of view, swarm behaviour is the collective motion of a large number of self-propelled entities. From the perspective of the mathematical modeller, it is an emergence behaviour arising from simple rules that are followed by individuals and does not involve any central coordination. Swarm behaviour is also studied by active matter physicists as a phenomenon which is not in thermodynamic equilibrium, and as such requires the development of tools beyond those available from the statistical physics of systems in thermodynamic equilibrium. In this regard, swarming has been compared to the mathematics of superfluids, specifically in the context of starling flocks (murmuration).
Swarm behaviour was first simulated on a computer in 1986 with the simulation program boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The model was originally designed to mimic the flocking behaviour of birds, but it can be applied also to schooling fish and other swarming entities.
The boids computer program, created by Craig Reynolds in 1986, simulates swarm behaviour following the above rules. Many subsequent and current models use variations on these rules, often implementing them by means of concentric "zones" around each animal. In the "zone of repulsion", very close to the animal, the focal animal will seek to distance itself from its neighbours to avoid collision. Slightly further away, in the "zone of alignment", the focal animal will seek to align its direction of motion with its neighbours. In the outermost "zone of attraction", which extends as far away from the focal animal as it is able to sense, the focal animal will seek to move towards a neighbour.
The shape of these zones will necessarily be affected by the sensory capabilities of a given animal. For example, the visual field of a bird does not extend behind its body. Fish rely on both vision and on hydrodynamic perceptions relayed through their , while Antarctic krill rely both on vision and hydrodynamic signals relayed through antennae.
However recent studies of starling flocks have shown that each bird modifies its position, relative to the six or seven animals directly surrounding it, no matter how close or how far away those animals are. Interactions between flocking starlings are thus based on a topological, rather than a metric, rule. It remains to be seen whether this applies to other animals. Another recent study, based on an analysis of high-speed camera footage of flocks above Rome and assuming minimal behavioural rules, has convincingly simulated a number of aspects of flock behaviour.
Swarm intelligence systems are typically made up of a population of simple agents such as boids interacting locally with one another and with their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of intelligent global behaviour, unknown to the individual agents.
Swarm intelligence research is multidisciplinary. It can be divided into natural swarm research studying biological systems and artificial swarm research studying human artefacts. There is also a scientific stream attempting to model the swarm systems themselves and understand their underlying mechanisms, and an engineering stream focused on applying the insights developed by the scientific stream to solve practical problems in other areas.
Simulations demonstrate that a suitable "nearest neighbour rule" eventually results in all the particles swarming together, or moving in the same direction. This emerges, even though there is no centralized coordination, and even though the neighbours for each particle constantly change over time. SPP models predict that swarming animals share certain properties at the group level, regardless of the type of animals in the swarm. Swarming systems give rise to emergent behaviours which occur at many different scales, some of which are both universal and robust. It has become a challenge in theoretical physics to find minimal statistical models that capture these behaviours.
Particle swarm optimization has been applied in many areas. It has few parameters to adjust, and a version that works well for a specific applications can also work well with minor modifications across a range of related applications.Hu X Particle swarm optimization: Tutorial. Retrieved 15 December 2010. A book by Kennedy and Eberhart describes some philosophical aspects of particle swarm optimization applications and swarm intelligence.
target="_blank" rel="nofollow"> Fossil 'conga lines' reveal origins of animal swarms National Geographic, 17 October 2019. as with the fly Leptoconops torrens. The findings suggest animal collective behaviour has very early evolutionary origins.
Examples of biological swarming are found in bird flocks,Feare C (1984) The Starling, Oxford University Press. . fish schools, , , molds, , quadruped Parrish JK and Hamner WM (eds) (1997) Animal Groups in Three Dimensions Cambridge University Press. . and people.
, unlike most ant species, do not construct permanent nests; an army ant colony moves almost incessantly over the time it exists, remaining in an essentially perpetual state of swarming. Several lineages have independently evolved the same basic behavioural and ecological syndrome, often referred to as "legionary behaviour", and may be an example of convergent evolution.
The successful techniques used by ant colonies have been studied in computer science and robotics to produce distributed and fault-tolerant systems for solving problems. This area of biomimetics has led to studies of ant locomotion, search engines that make use of "foraging trails", fault-tolerant storage and networking algorithms.
Cockroaches are mainly nocturnal and will run away when exposed to light. A study tested the hypothesis that cockroaches use just two pieces of information to decide where to go under those conditions: how dark it is and how many other cockroaches there are. The study conducted by José Halloy and colleagues at the Free University of Brussels and other European institutions created a set of tiny that appear to the roaches as other roaches and can thus alter the roaches' perception of critical mass. The robots were also specially scented so that they would be accepted by the real roaches.
Swarming in locusts has been found to be associated with increased levels of serotonin which causes the locust to change colour, eat much more, become mutually attracted, and breed much more easily. Researchers propose that swarming behaviour is a response to overcrowding and studies have shown that increased tactile stimulation of the hind legs or, in some species, simply encountering other individuals causes an increase in levels of serotonin. The transformation of the locust to the swarming variety can be induced by several contacts per minute over a four-hour period. Blocking 'happiness' chemical may prevent locust plagues, New Scientist, 2009-01-29, accessed 2009-01-31 Notably, an innate predisposition to aggregate has been found in hatchlings of the desert locust, Schistocerca gregaria, independent of their parental phase.
An individual locust's response to a loss of alignment in the group appears to increase the randomness of its motion, until an aligned state is again achieved. This noise-induced alignment appears to be an intrinsic characteristic of collective coherent motion.
Monarch butterflies are especially noted for their lengthy annual migration. In North America they make massive southward migrations starting in August until the first frost. A northward migration takes place in the spring. The monarch is the only butterfly that migrates both north and south as the birds do on a regular basis. But no single individual makes the entire round trip. Female monarchs deposit eggs for the next generation during these migrations.Pyle, Robert Michael, "National Audubon Society Field Guide to North American Butterflies", p712-713, Alfred A. Knopf, New York, The length of these journeys exceeds the normal lifespan of most monarchs, which is less than two months for butterflies born in early summer. The last generation of the summer enters into a non-reproductive phase known as diapause and may live seven months or more. During diapause, butterflies fly to one of many overwintering sites. The generation that overwinters generally does not reproduce until it leaves the overwintering site sometime in February and March. It is the second, third and fourth generations that return to their northern locations in the United States and Canada in the spring. How the species manages to return to the same overwintering spots over a gap of several generations is still a subject of research; the flight patterns appear to be inherited, based on a combination of the position of the sun in the skyGugliotta, Guy (2003): Butterflies Guided By Body Clocks, Sun Scientists Shine Light on Monarchs' Pilgrimage . Washington Post, May 23, 2003, page A03. Retrieved 2006-JAN-07. and a time-compensated Sun compass that depends upon a circadian clock that is based in their antennae.
Many birds migrate in flocks. For larger birds, it is assumed that flying in flocks reduces energy costs. The V formation is often supposed to boost the efficiency and range of flying birds, particularly over long bird migration routes. All the birds except the first fly in the upwash from one of the wingtip vortices of the bird ahead. The upwash assists each bird in supporting its own weight in flight, in the same way a glider aircraft can climb or maintain height indefinitely in rising air. Geese flying in a V formation save energy by flying in the updraft of the wingtip vortex generated by the previous animal in the formation. Thus, the birds flying behind do not need to work as hard to achieve lift. Studies show that birds in a V formation place themselves roughly at the optimum distance predicted by simple aerodynamic theory. Drag Reduction from Formation Flight. Flying Aircraft in Bird-Like Formations Could Significantly Increase Range; Defense Technical Information Center; April 2002; Retrieved February 27, 2008 Geese in a V-formation may conserve 12–20% of the energy they would need to fly alone. and were found in radar studies to fly 5 km per hour faster in flocks than when they were flying alone. The birds flying at the tips and at the front are rotated in a timely cyclical fashion to spread flight fatigue equally among the flock members. The formation also makes communication easier and allows the birds to maintain visual contact with each other.
Other animals may use similar drafting techniques when migrating. , for example, migrate in close single-file formation "lobster trains", sometimes for hundreds of miles.
The Mediterranean and other seas present a major obstacle to soaring birds, which must cross at the narrowest points. Massive numbers of large raptors and storks pass through areas such as Gibraltar, Falsterbo, and the Bosphorus at migration times. More common species, such as the European honey buzzard, can be counted in hundreds of thousands in autumn. Other barriers, such as mountain ranges, can also cause funnelling, particularly of large diurnal migrants. This is a notable factor in the migratory bottleneck. This concentration of birds during migration can put species at risk. Some spectacular migrants have already gone extinct, the most notable being the passenger pigeon. During migration the flocks were a mile (1.6 km) wide and 300 miles (500 km) long, taking several days to pass and containing up to a billion birds.
Fish derive many benefits from shoaling behaviour including defence against predators (through better predator detection and by diluting the chance of capture), enhanced foraging success, and higher success in finding a mate.Pitcher TJ and Parish JK (1993) "Functions of shoaling behaviour in teleosts" In: Pitcher TJ (ed) Behaviour of teleost fishes. Chapman and Hall, New York, pp 363–440 It is also likely that fish benefit from shoal membership through increased hydrodynamic efficiency.Hoare DJ, Krause J, Peuhkuri N and Godin JGJ (2000) Body size and shoaling in fish Journal of Fish Biology, 57(6) 1351-1366.
Fish use many traits to choose shoalmates. Generally they prefer larger shoals, shoalmates of their own species, shoalmates similar in size and appearance to themselves, healthy fish, and kin (when recognised). The "oddity effect" posits that any shoal member that stands out in appearance will be preferentially targeted by predators. This may explain why fish prefer to shoal with individuals that resemble them. The oddity effect would thus tend to homogenise shoals.
One puzzling aspect of shoal selection is how a fish can choose to join a shoal of animals similar to themselves, given that it cannot know its own appearance. Experiments with zebrafish have shown that shoal preference is a learned ability, not innate. A zebrafish tends to associate with shoals that resemble shoals in which it was reared, a form of imprinting.
Other open questions of shoaling behaviour include identifying which individuals are responsible for the direction of shoal movement. In the case of fish migration movement, most members of a shoal seem to know where they are going. In the case of foraging behaviour, captive shoals of golden shiner (a kind of minnow) are led by a small number of experienced individuals who knew when and where food was available.
Radakov estimated herring schools in the North Atlantic can occupy up to with fish densities between 0.5 and 1.0 fish/cubic metre, totalling several billion fish in one school.Radakov DV (1973) Schooling in the ecology of fish. Israel Program for Scientific Translation, translated by Mill H. Halsted Press, New York.
target="_blank" rel="nofollow"> "The structure and function of fish schools" Scientific American, June:114–123.
Later work suggested that swimming activity in krill varied with stomach fullness. Satiated animals that had been feeding at the surface swim less actively and therefore sink below the mixed layer. As they sink they produce faeces which may mean that they have an important role to play in the Antarctic carbon cycle. Krill with empty stomachs were found to swim more actively and thus head towards the surface. This implies that vertical migration may be a bi- or tri-daily occurrence. Some species form surface swarms during the day for feeding and reproductive purposes even though such behaviour is dangerous because it makes them extremely vulnerable to predators.Howard, D.: " Krill", pp. 133–140 in Karl, H.A. et al. (eds): Beyond the Golden Gate – Oceanography, Geology, Biology, and Environmental Issues in the Gulf of the Farallones, USGS Circular 1198, 2001. URLs last accessed 2010-06-04. Dense swarms may elicit a feeding frenzy among fish, birds and mammal predators, especially near the surface. When disturbed, a swarm scatters, and some individuals have even been observed to ecdysis instantaneously, leaving the exuvia behind as a decoy. In 2012, Gandomi and Alavi presented what appears to be a successful stochastic algorithm for modelling the behaviour of krill swarms. The algorithm is based on three main factors: " (i) movement induced by the presence of other individuals (ii) foraging activity, and (iii) random diffusion."
Copepods also swarm. For example, monospecific swarms have been observed regularly around and sea grass, and in lakes. Swarms densities were about one million copepods per cubic metre. Typical swarms were one or two metres in diameter, but some exceeded 30 cubic metres. Copepods need visual contact to keep together, and they disperse at night.
Spring produces algal bloom of swarming phytoplankton which provide food for copepods. Planktonic copepods are usually the dominant members of the zooplankton, and are in turn major food organisms for many other marine animals. In particular, copepods are prey to forage fish and jellyfish, both of which can assemble in vast, million-strong swarms. Some copepods have extremely fast when a predator is sensed and can jump with high speed over a few millimetres (see animated image below).
Planktonic copepods are important to the carbon cycle. Some scientists say they form the largest animal biomass on earth. They compete for this title with Antarctic krill. Because of their smaller size and relatively faster growth rates, however, and because they are more evenly distributed throughout more of the world's oceans, copepods almost certainly contribute far more to the secondary productivity of the world's oceans, and to the global ocean carbon sink than krill, and perhaps more than all other groups of organisms together. The surface layers of the oceans are currently believed to be the world's largest carbon sink, absorbing about 2 billion tonnes of carbon a year, the equivalent to perhaps a third of greenhouse gas, thus reducing their impact. Many planktonic copepods feed near the surface at night, then sink into deeper water during the day to avoid visual predators. Their moulted exoskeletons, faecal pellets and respiration at depth all bring carbon to the deep sea.
, in particular, display observable swarm behavior, growing in patterns that exceed the statistical threshold for random probability, and indicate the presence of communication between individual root apexes. The primary function of plant roots is the uptake of , and it is this purpose which drives swarm behavior. Plants growing in close proximity have adapted their growth to assure optimal nutrient availability. This is accomplished by growing in a direction that optimizes the distance between nearby roots, thereby increasing their chance of exploiting untapped nutrient reserves. The action of this behavior takes two forms: maximization of distance from, and repulsion by, neighboring root apexes. The transition zone of a root tip is largely responsible for monitoring for the presence of soil-borne hormones, signaling responsive growth patterns as appropriate. Plant responses are often complex, integrating multiple inputs to inform an autonomous response. Additional inputs that inform swarm growth includes light and gravity, both of which are also monitored in the transition zone of a root's apex. These forces act to inform any number of growing "main" roots, which exhibit their own independent releases of inhibitory chemicals to establish appropriate spacing, thereby contributing to a swarm behavior pattern. Horizontal growth of roots, whether in response to high mineral content in soil or due to stolon growth, produces branched growth that establish to also form their own, independent root swarms.
The mathematical modelling of flocking behaviour is a common technology, and has found uses in animation. Flocking simulations have been used in many films to crowd simulation which move realistically. Tim Burton's Batman Returns was the first movie to make use of swarm technology for rendering, realistically depicting the movements of a group of bats using the boids system. The Lord of the Rings film trilogy made use of similar technology, known as Massive, during battle scenes. Swarm technology is particularly attractive because it is cheap, robust, and simple.
An ant-based computer simulation using only six interaction rules has also been used to evaluate aircraft boarding behaviour.Livermore R (2008) "A multi-agent system approach to a simulation study comparing the performance of aircraft boarding using pre-assigned seating and free-for-all strategies" Open University, Technical report No 2008/25. Airlines have also used ant-based routing in assigning aircraft arrivals to airport gates. An airline system developed by Douglas A. Lawson uses swarm theory, or swarm intelligence—the idea that a colony of ants works better than one alone. Each pilot acts like an ant searching for the best airport gate. "The pilot learns from his experience what's the best for him, and it turns out that that's the best solution for the airline," Lawson explains. As a result, the "colony" of pilots always go to gates they can arrive and depart quickly. The program can even alert a pilot of plane back-ups before they happen. "We can anticipate that it's going to happen, so we'll have a gate available," says Lawson. "Planes, Trains and Ant Hills: Computer scientists simulate activity of ants to reduce airline delays" Science Daily, 1 April 2008.
Swarm behaviour occurs also in traffic flow dynamics, such as the traffic wave. Bidirectional traffic can be observed in ant trails. In recent years this behaviour has been researched for insight into pedestrian and traffic models. Are we nearly there yet? Motorists could learn a thing or two from ants The Economist, 10 July 2009. Simulations based on pedestrian models have also been applied to crowds which stampede because of panic.
Herd behaviour in marketing has been used to explain the dependencies of customers' mutual behaviour. The Economist reported a recent conference in Rome on the subject of the simulation of adaptive human behaviour. It shared mechanisms to increase impulse buying and get people "to buy more by playing on the herd instinct." The basic idea is that people will buy more of products that are seen to be popular, and several feedback mechanisms to get product popularity information to consumers are mentioned, including smart card technology and the use of RFID technology. A "swarm-moves" model was introduced by a Florida Institute of Technology researcher, which is appealing to supermarkets because it can "increase sales without the need to give people discounts."
Partially inspired by colonies of insects such as ants and bees, researchers are modelling the behaviour of swarm robotics of thousands of tiny robots which together perform a useful task, such as finding something hidden, cleaning, or spying. Each robot is quite simple, but the emergent behaviour of the swarm is more complex. (2025). 9789812877505, Springer. ISBN 9789812877505 The whole set of robots can be considered as one single distributed system, in the same way an ant colony can be considered a superorganism, exhibiting swarm intelligence. The largest swarms so far created is the 1024 robot Kilobot swarm. Other large swarms include the iRobot swarm, the SRI International/ActivMedia Robotics Centibots project, and the Open-source Micro-robotic Project swarm, which are being used to research collective behaviours. Swarms are also more resistant to failure. Whereas one large robot may fail and ruin a mission, a swarm can continue even if several robots fail. This could make them attractive for space exploration missions, where failure is normally extremely costly. In addition to ground vehicles, swarm robotics includes also research of swarms of and heterogeneous teams of ground and aerial vehicles.
In contrast macroscopic robots, colloidal particles at microscale can also be adopted as agents to perform collective behaviors to conduct tasks using mechanical and physical approaches, such as reconfigurable tornado-like microswarm mimicking schooling fish, hierarchical particle species mimicking predating behavior of mammals, micro-object manipulation using a transformable microswarm. The fabrication of such colloidal particles is usually based on chemical synthesis.
Merely because multiple units converge on a target, they are not necessarily swarming. Siege operations do not involve swarming, because there is no manoeuvre; there is convergence but on the besieged fortification. Nor do guerrilla ambushes constitute swarms, because they are "hit-and-run". Even though the ambush may have several points of attack on the enemy, the guerillas withdraw when they either have inflicted adequate damage, or when they are endangered.
In 2014 the U. S. Office of Naval Research released a video showing tests of a swarm of small autonomous drone attack boats that can steer and take coordinated offensive action as a group. U.S. Navy could 'swarm' foes with robot boats, CNN, 13 October 2014.
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