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Principle of Stigmergy

Stigmergy is a core principle behind the phenomenon of swarm intelligence. It is a method of indirect communication and collective stimulation in emergent systems in which the individual parts of the system communicate with one another by modifying their local environment. In other words it is a social phenomenon in which agents organize themselves by affecting their environment rather than communicating directly one to another. The agents do their work and are at the same time organized by (the result and product of) this work.

The term was introduced by French biologist Pierre-Paul Grassé who studied the ways that ant and termite colonies work. He defined it as: "Stimulation of workers by the performance they have achieved." Grasse showed that a particular configuration of a termite’s environment, for example the building and maintaining of a nest, triggered a response in a termite to modify the environment. The resulting modification in turn stimulated other responses which further transformed the environment. Therefore it is the nest itself which regulates and coordinates its own construction. In a special issue of the journal Artificial Life on stigmergy, Eric Bonabeau said:

"The concept of stigmergy was introduced by Pierre-Paul Grasse in the 1950's to describe the indirect communication taking place among individuals in social insect societies. Stigmergy was originally defined by Grasse in his studies on the reconstruction of termite nests. Grasse showed that the regulation and coordination of the building activity do not depend on the workers themselves but is mainly achieved by the nest: a stimulating configuration triggers a response of a termite worker, transforming the configuration into another configuration that may trigger in turn another, possibly different, action performed by the same termite or any other worker in the colony."

It is now also employed in experimental research in robotics, multi-agent system and communication in computer networks. The name comes from the Greek stigma (sting, goad, stimulation) and ergon (work, product of labor) and means therefore literally "stimulating product of labour". It was introduced to explain collective task coordination and regulation in the context of nest construction among termites.

Stigmergy was first observed in nature; for example, termites and ants communicate to one another to find and collect food (foraging process) by laying down pheromones along their trails (see the NetLogo Ant Model). Another common example is nest-building in termites. Termites also use pheromones to build very complex structures by following a simple decentralized rule set. Each insect scoops up a 'mudball' or similar material from its environment, invests the ball with pheromones, and deposits it on the ground. Termites are attracted to their nestmates' pheromones and are therefore more likely to drop their own mudballs near their neighbors'. Over time this leads to the construction of pillars, arches, tunnels and chambers. Clustering can be observed even in a much simpler system (see the NetLogo Termites Model or here). To build a single termite mound in an environment consisting of randomly-scattered wood chips, a group of termites each has only to follow one simple rule :

While wandering randomly
-if you find a chip then pick it up
-unless you're already carrying a chip in which case drop it 

Stigmergy is also demonstrated by the internet in which users communicate with each other by modifying their shared virtual environment. This wiki is a perfect example! The massive structure of information available here could be compared to a termite nest; one initial user leaves a seed of an idea (a mudball) which attracts other users who then build upon and modify this initial concept eventually constructing an elaborate structure of connected thoughts.


  • 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
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