Swarm Intelligence

Swarm Intelligence (SI) systems are made up of a population of simple agents interacting locally with their neighbours and environment. SI systems has no centralized control structure dictating how individual agents should behave, local interactions between such agents often lead to the emergence of global behavior. Examples of systems like this can be found in nature, including ant colonies, bird flocking, animal herding, bacteria molding and fish schooling. These population based stochastic optimization technique was developed by Dr. Eberhart and Dr. Kennedy in 1995.

SI systems are divided into Ant colony optimization (ACO) , Stochastic diffusion search (SDS) or Particle swarm optimization (PSO). All these systems use the same idea of collective intelligence which emerge from local interactions among the agents. SI systems have already been applied successfully to solve real-world optimization problems in engineering and telecommunication. SI models have many features in common with Evolutionary Systems.