Swarm intelligence is the term used to denote artificial intelligence systems where collective behavior of simple agents causes coherent solutions or patterns to emerge. This has applications in swarm robotics.

A population of unsophisticated agents interacting with their environments and each other makes up a swarm intelligence system. Because there is no set of global instructions on how these units act, the collective interactions of all the agents within the system often leads into some sort of collective behavior or intelligence.

This type of artificial intelligence is used to explore distributed problem solving without having a centralized control structure. This is seen to be a better alternative to centralized, rigid and preprogrammed control. Real life swarm intelligence can be observed in ant colonies, beehives, bird flocks and animal herds.

Examples of Swarm Intelligence Systems

Ant colony behavior

Ant colony behavior has been one of the most popular models of swarm behavior. Ants by themselves may seem to act randomly and without any discernible purpose, but when the collective interactions among ants are taken together, there will emerge a collective intelligence and behavior that has the capacity of solving a lot of problems. Through swarm intelligence, ants can determine the shortest path to a food source, feed the whole colony, build large structures, and adapt to situations.

The swarm intelligence model of ant colonies has already been applied to technology in recent years such as in routing optimization of communication networks, decentralized control of UAVs and factory scheduling.Swarm Intelligence

Particle swarm optimization

Particle swarm optimization, on the other hand, is a type of swarm intelligence inspired by bird flocks and fish schools. This type of swarm optimization gives individual agents within the swarm the ability to change its position depending on its own limited intelligence and in comparison to other agents in the population. This enables individual agents to modify their paths depending on the success of the other agents in the population in finding the correct solution.

This type of swarm intelligence is used in practical applications such as in artificial neural networks and in grammatical evolution models.

Stochastic diffusion search

This type of swarm intelligence is based on the tandem-calling mechanism used by a variety of ants. However, it is different from the abovementioned swarm intelligence system in the sense that this requires one-to-one interactions between the elements of the population in order to exchange individual partial hypothesis on likely solutions to a problem. Individual agents then update their own preferences while randomly testing new hypotheses. This process culminates in a collective or sub-collective choice of the optimal solution.

Applications of Artificial Swarm Intelligence

Swarm intelligence has applications in decentralized controls of unmanned vehicles for the military so single operators can control more unmanned vehicles. The use of swarm intelligence in medical nanobots may also help combat cancer. Swarm intelligence was used in the creation of the video sequence "Battle of Helm's Deep" in the movie, Lord of the Rings. As mentioned previously, swarm intelligence can also be used in communication networks optimization.