Swarm intelligence

Swarm intelligence is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.

SI systems consist typically of a population of simple agents or boids interacting locally with one another and with their environment. The inspiration often comes from nature, especially biological systems. 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, interactions between such agents lead to the emergence of "intelligent" global behavior, unknown to the individual agents. Examples of swarm intelligence in natural systems include ant colonies, bird flocking, hawks hunting, animal herding, bacterial growth, fish schooling and microbial intelligence.

The application of swarm principles to robots is called swarm robotics while swarm intelligence refers to the more general set of algorithms. Swarm prediction has been used in the context of forecasting problems. Similar approaches to those proposed for swarm robotics are considered for genetically modified organisms in synthetic collective intelligence.

Properties of a Swarm Intelligence System

The typical swarm intelligence system has the following properties:

• It is composed of many individuals.
• The individuals are relatively homogeneous (i.e., they are either all identical or they belong to a few typologies).
• The interactions among the individuals are based on simple behavioral rules that exploit only local information that the individuals exchange directly or via the environment.
• The overall behaviour of the system results from the interactions of individuals with each other and with their environment, that is, the group behavior self-organizes.

Studies and Applications of Swarm Intelligence

Nest Building Behavior of Wasps and Termites: Wasps build nests with a highly complex internal structure that is well beyond the cognitive capabilities of a single wasp. Termites build nests whose dimensions (they can reach many meters of diameter and height) are enormous when compared to a single individual, which can measure as little as a few millimeters.

Flocking and Schooling in Birds and Fish

Flocking and schooling are examples of highly coordinated group behaviors exhibited by large groups of birds and fish. Scientists have shown that these elegant swarm-level behaviors can be understood as the result of a self-organized process where no leader is in charge and each individual bases its movement decisions solely on locally available information

Swarm-based Network Management

The first swarm-based approaches to network management were proposed in 1996 by Schoonderwoerd et al. and in 1998 by Di Caro and Dorigo. Schoonderwoerd et al. proposed Ant-based Control (ABC), an algorithm for routing and load balancing in circuit-switched networks; Di Caro and Dorigo proposed AntNet, an algorithm for routing in packet-switched networks.

 Particle swarm optimization

Particle swarm optimization (PSO) is accepted as the second population-based algorithm inspired from animals. Since James Kennedy is a social psychologist and Russell C. Eberhart simulated the bird flocking and fish schooling foraging behaviors, they have used this simulation to the solution of an optimization problem and published their idea in a conference in 1995 for the optimization of continuous nonlinear functions.

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International journal of swarm intelligence and evolutionary computation

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