Abstract

Swarm Intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The inspiration often comes from nature, especially biological systems. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems. SI systems are typically made up of a population of simple agents or boids interacting locally with one another and their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interaction between such agents lead to the emergence of “intelligent” global behavior, unknown to the individual agents. Swarm Intelligence is a relatively new paradigm being applied in a host of research settings to improve the management and control of large numbers of interacting entities such as communications, computer and sensor networks, satellite constellations and more. Attempts to take advantage of this paradigm and mimic the behavior of insect swarms however often lead to many different implementations of SI. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth and fish schooling. This article provides a set of general principle of Swarm Intelligence.

Keyword

Swarm intelligence, SI, self-organized, agents, ANN, GSA, IWD.

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