“Insects that live in colonies – ants, bees, wasps, termites – have long fascinated everyone from naturalists to artists. Maurice Maeterlinek, the Belgian poet, once wrote, “What is that governs here? What is it that issues orders, foresees the future, elaborates plans and preserves equilibrium?” These indeed are puzzling questions.” [Bonabeau, “Swarm Smarts”, pg73]
What is a swarm? What is swarm
intelligence? How can it be applied to solve problems?
A swarm is a large number of insects or other organisms in motion.
"Swarm Intelligence is a
property of systems of unintelligent agents exhibiting collectively intelligent
The power of Ants
To be able to
fully understand the power of Swarm Intelligence and how it can be applied to
our network routing problem, we have to study what a swarm of insects can do by
working together in a community. If
we look closely at one single ant, we can observe that it's a simple
unsophisticated insect that performs repetitive actions, which don't show much
signs of cognition nor intelligence. The
single ant seems to have its own agenda. Now if we look at a collection of ants, we can see that these
first overlooked insects can manage when working together important tasks and
seem to have a special link or communication system between them.
Several studies of ants and ant colonies have shown that they can
collectively solve problems and perform complicated tasks.
Several are shown below:
Ants show two basic types of stigmergy (indirect communication through the environment):
· Sematectonic: actions of one agent directly solving problems, which affect other agents.
· Sign based: actions of agents affecting the environment.
Swarm Intelligence is modeled after the study of behavioral patterns of biological entities that live in colonies like insects, bees, wasps, termites and ants. Swarm agents try to imitate in software the behavior of these insects one by one and then, when grouped together they can solve multiple problems. In order to model correctly these insects, the modeler must analyze in detail not only the actions and patterns of a single insect, but also of a whole swarm of insects.
The swarm has the following characteristics:
· Decentralized: the system has no central control, it is highly adaptive and can adapt fast to changes in the environment.
· Ecologist view of perception: the entities in the system have no pre-built or defined information about the environment. They "learn as the go". This is very important in networking because as systems are added into the network, the routers will have to learn and adapt to the changes, in other words, be dynamic. If routing agents are modeled after swarms they can obtain these properties and apply them as needed..
Examples of Swarm Intelligence
Copyright 2001: Ivan A. Escobar Broitman