Swarm Intelligence

'''Swarm Intelligence''' is a form of [[Collective Intelligence|collective intelligence]] in [[Swarm|swarms]]. It is a general term of the flexible, adaptive and collective behavior found in swarms, flocks, herds and other groups of social animals, especially for social insects such as ants, termites, locusts, wasps, and honey bees. Examples of systems with swarm intelligence can be found in all kind of animal groups: schools of fish, flocks of birds, herds of land animals.

[[Image:SwarmIntelligence.png|thumb|500px|Swarm-Intelligence in relation to stigmergy, swarm-formation and emergence]]

== Definition and History ==

Systems which exhibit swarm intelligence are composed of many individuals coordinated by decentralized control and self-organization. Swarm Intelligence is traditionally understood as "the [[Emergence|emergent]] collective intelligence of groups of simple [[Agent|agents]]" (Bonabeau et al. 1999). It is the typical example of [[Emergence|emergence]] and [[Emergence|emergent phenomena]]. The expression "swarm intelligence" was introduced by G. Beni and U. Wang in 1989, in the context of cellular robotic systems. In these systems many simple agents occupy one- or two-dimensional environments to generate patterns and self-organize through nearest-neighbor interactions. Bonabeau, Dorigo and Theraulaz extend Beni et al.'s definition in their "Swarm Intelligence" book, and include any attempt to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies and other animal societies. 

== Forms and Relations ==

{{SelfOrg}}

The concept of swarm intelligence is related to the two basic concepts of [[Stigmergy|stigmergy]] and [[Emergence|emergence]], which describe the appearance of organized behavior patterns in groups of individuals. A group of individuals follows the "acts as one" or "acts as swarm" pattern: fireflies flashing in synchrony follow the rule, “I signal when you signal”, fish traveling in schools abide by the rule, “I go where you go”, birds flying in [[Flocking|flocks]] follow the rule "I fly where you fly" and so forth. Coordination of collective behavior is not possible without communication. This communication is of course not always evident and visible. Sometimes the communication takes place in a direct way (for example by visual contact), sometimes the communication happens indirectly with the help of the environment (for example by invisible scents).

[[Image:swarm_intelligence_and_stigmergy.png|left|thumb|400px|Swarm-Formation vs. Swarm-Intelligence]]

There are two basic forms of swarm intelligence: (1) swarm-formation and (2) stigmergy. The term swarm-formation describes the first basic form of swarm intelligence and characterizes the creation of swarms, [[Flocking|flocks]] or groups by direct interaction, as it can be observed in flocks of birds, schoals of fish, etc. The rules are simple: stay close to the group, but don't come too close to individuals. The principle of swarm formation is based on a distinction between global and local, group and agent, swarm and individual: global attraction (move towards the group) combined with local repulsion (stay aways from individuals). It can be described by the [[Boids_Model|boids model]] of Craig Reynolds.

[[Stigmergy]] is the second basic form of swarm intelligence. Swarm intelligence and [[Stigmergy|stigmergy]] are often used synonymously and describe swarms and groups which are controlled by indirect interaction over the environment, for example in ant colonies. Ant colonies and other social insects use pheromones and scents to communicate with each other. This form of volatile communication allows the dynamic construction of trails for foraging, and enable a good trade-off between [[Exploitation_and_Exploration|exploitation and exploration]] of food sources in the surrounding environment.

While the principle of stigmergy explains for example trail formation with the purpose of collective foraging, the principle of swarm formation explains the aggregation and group formation with the purpose of collective movement. Both forms and principles can be considered as a case of emergence. [[Emergence|Emergence]] is the general term which describes the appearance of macroscopic phenomena out of mircoscopic interactions.

== Examples ==

Large animal groups with coordinated movement such as swarms, herds, 
schools, and flocks are widespread phenomena in biology.
These coherent, large-scale groups often bring negative consequences for
the individual (increased competition for resources, disease transmission, 
and attention from predators), but also benefits (more effective foraging, 
reproduction, migration, diluting the chance of capture and escape from 
predators).

The advantage a swarm offers is often in a delicate balance by a disadvantage.
The swarm can detect a predator better than an individual, but
the predator can also detect a swarm better than a individual animal.
A swarm can detect a food source better than an individual, but
it also exploits it much faster than any individual 

The coordination relies often on a kind of language, although it can be an unusual one.
Honeybees perform a dance on their return to the hive, known as bee dance or waggle dance.
The information contained in this "dance language" is used to select a new nest site or to 
exploit a new food source. 
Ants and other insects communicate mainly through "chemical languages": pheromones
and other chemical scents and substances.

* nest building of social insects (wasps, termites: pheromones)
* path finding and food foraging (ants, locusts: pheromones)
* nest site search and nectar foraging (honey bees: waggle dance)
* collective sorting and clustering (ants: change of environment,stigmergy)
* group defense

Among locusts (grashoppers) swarming behaviour is partially a 
response to overcrowding. When large numbers of locusts are forced 
together in a small area, they being to form a swarm that can travel long 
distances consuming lots of vegetation. The critical tipping point is around
20 insects per square metre. Swarms of locusts can be a plague,
because they consume vast amounts of crops.

A swarm of locusts allows more effective migration and travel.
Each member of the swarm expends less energy than a single 
locust would spend in normal individual flight. Contrary to
individual locusts, locust swarms can travel up to 100km or 
more in a single day.

== Advantages and drawbacks ==

The fascinating thing about swarm intelligence 
is that complex collective behavior emerges 
from individuals following simple rules. 
Swarm-intelligence and emergence are fascinating 
because this is not expected or usual behavior,
and the system is fault-tolerant and robust.
The idea of emergence is that simple underlying rules
'''can''' give rise to surprisingly complex structures. 
A system '''can''' evolve a large structure from repeated 
small-scale interactions between its smaller elements.
But simple rules do not always lead to complex 
structures. Individuals following simple rules usually 
do not organize themselves at all if there is no
suitable communication and coordination, they lead 
to simple collective behavior or chaos and 
confusion. True self-organization is the EXCEPTION,
not the RULE. It happens rarely and not 
frequently. 

Sometimes there are indeed forms and patterns which
emerge from simple rules, but usually they are as simple 
as heaps, dunes or ripples. not more. An ant colony
has the form of a heap and the ants are forming "streets".
This is it, they are not building any other complex
structures. The result of countless repeated, 
small-scale interactions often is not a big, 
global structure, rather a big mess. There are only 
a few interesting examples of self-organization: 
the flock of birds, the ant colony, etc.

Successfully identifying self-organizing systems 
with swarm intelligence or emergent properties is a bit
like lost finding ancient cities or sunken ships with lots of gold.
They are interesting, fascinating and appealing, sometimes
even mysterious. Everybody would like to find or have them,
but it is not easy, the obstacles are very high, and the
interesting cases are very rare and mostly well-known.
Therefore the search for both can be frustrating (in
exceptional cases also very rewarding and pleasing).
Moreover you don't now what you will see until you watch it
yourself, and even if you do, in the interesting cases you
don't know exactly why it has become this way.

Perhaps swarm intelligence would be less mysterious and
fascinating if we could perceive the language which is
used to control it directly, for example if we could 
perceive the odors and chemicals directly which are used 
by ants for communication. Unlike ants we do not communicate 
with chemicals.

== Scientists and Labs ==

Software and Optimization

* [http://iridia.ulb.ac.be/~mdorigo/HomePageDorigo/ Marco Dorigo]
* [http://www.idsia.ch/~luca/ Luca Maria Gambardella]
* [http://hampshire.edu/~lasCCS/ Lee Spector]

Software and Hardware:

* [http://www.unm.edu/~tanner/ Herbert Glenn Tanner]

Hardware and Robotics:

* [http://lis.epfl.ch/member.php?SCIPER=111729 Dario Floreano]
* [http://www5.epfl.ch/swis/page1336.html Alcherio Martinoli]

Biology 

* [http://www.stanford.edu/~dmgordon/ Deborah Gordon and The Gordon Lab]
* [http://www.princeton.edu/~icouzin/ Iain D. Couzin] and the [http://icouzin.princeton.edu/ Couzin Lab]

==Articles==

Many articles and resources can be found [http://dsp.jpl.nasa.gov/members/payman/swarm/ here].

* Ashley J.W. Ward et al., [http://www.pnas.org/content/108/6/2312.full Fast and accurate decisions through collective vigilance in fish shoals], PNAS Vol. 108 No. 6 (2011) 2312-2315
* Iain D. Couzin, [http://www.princeton.edu/~icouzin/Couzin2009.pdf Collective cognition in animal groups], Trends Cogn Sci 13 (2009) 36–43.
* G. Beni and U. Wang, ''Swarm intelligence in cellular robotic systems'', In NATO Advanced Workshop on Robots and Biological Systems, Il Ciocco, Tuscany, Italy, 1989.
* Herbert G. Tanner, Ali Jadbabaie and George J. Pappas, [http://citeseer.ist.psu.edu/tanner03stable.html Stable Flocking of Mobile Agents, Part I: Fixed Topology], [http://citeseer.ist.psu.edu/563430.html Part II: Dynamic Topology], 2003
* [http://citeseer.ist.psu.edu/mataric95designing.html Designing and Understanding Adaptive Group Behavior] Maja J. Mataric, 1995
* Andrea Perna et al., [http://arxiv.org/abs/1201.5827 Individual rules for trail pattern formation in Argentine ants (Linepithema humile)], http://arxiv.org/abs/1201.5827

Dance languages and nest site search of honey bees

* [http://bees.ucr.edu/reprints/nature421.pdf How Self-Organization Evolves], P. Kirk Visscher, Nature Vol. 421 (2003) 799-800
* [http://bees.ucr.edu/reprints/nature397.pdf Collective decisions and cognition in bees], P. Kirk Visscher, Scott Camazine, Nature Vol. 397 (1999) 400
* [http://bees.ucr.edu/reprints/eoi.pdf Dance Language], P. Kirk Visscher, in V.H. Resh and R. T. Cardé, eds. Encyclopedia of Insects. Academic Press (2003) pp. 284-288

==Books==

* Marco Dorigo, Thomas Stützle, ''Ant Colony Optimization'' (2004) The MIT Press, ISBN 0262042193 

* Eric Bonabeau, Marco Dorigo, Guy Theraulaz, ''Swarm Intelligence: From Natural to Artificial Systems'' (1999) Oxford University Press, ISBN 0195131592

* Scott Camazine et al., ''Self-Organization in Biological Systems'' (2003) Princeton University Press, ISBN 0691116245

* James Kennedy and Russell C. Eberhart, ''Swarm Intelligence'', (2001) Morgan Kaufmann, ISBN 1558605959

* Mitchel Resnick, ''Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds'' (1997) The MIT Press, ISBN 0262181622

== Links ==

* Wikipedia entry for [http://en.wikipedia.org/wiki/Swarm_behaviour swarm behaviour]
* Wikipedia entry for [http://en.wikipedia.org/wiki/Collective_animal_behaviour collective animal behaviour]

[[Category:Basic Principles]] [[Category:Collective Processes]]