Such systems are made up by a population of simple agents interacting locally with one other and with their environment. Although there is typically no centralised control dictating the behaviour of the agents, local interactions ong the agents often cause a global pattern to emerge. Examples of systems like this can be found in nature, including ant colonies, bird flocking, animal herding, honey bees, bacteria, and many more. Swarm-like algorithms, such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), have already been applied successfully to solve real-world optimization problems in engineering and telecommunication. SI models have many features in common with Evolutionary Algorithms.
posted by Marcus Zillman |
11:09 AM
