Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligence are colonies of ants and termites, schools of fish, flocks of birds, herds of land animals. Some human artifacts also fall into the domain of swarm intelligence, notably some multi-robot systems, and also certain computer programs that are written to tackle optimization and data analysis problems.

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 (stigmergy);
• 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.

The characterizing property of a swarm intelligence system is its ability to act in a coordinated way without the presence of a coordinator or of an external controller. Many examples can be observed in nature of swarms that perform some collective behavior without any individual controlling the group, or being aware of the overall group behavior. Notwithstanding the lack of individuals in charge of the group, the swarm as a whole can show an intelligent behavior. This is the result of the interaction of spatially neighboring individuals that act on the basis of simple rules.

Most often, the behavior of each individual of the swarm is described in probabilistic terms: Each individual has a stochastic behavior that depends on his local perception of the neighborhood.

Because of the above properties, it is possible to design swarm intelligence system that are scalable, parallel, and fault tolerant.

• Scalability means that a system can maintain its function while increasing its size without the need to redefine the way its parts interact. Because in a swarm intelligence system interactions involve only neighboring individuals, the number of interactions tends not to grow with the overall number of individuals in the swarm: each individual's behavior is only loosely influenced by the swarm dimension. In artificial systems, scalability is interesting because a scalable system can increase its performance by simply increasing its size, without the need for any reprogramming.
• Parallel action is possible in swarm intelligence systems because individuals composing the swarm can perform different actions in different places at the same time. In artificial systems, parallel action is desirable because it can help to make the system more flexible, that is, capable to self-organize in teams that take care simultaneously of different aspects of a complex task.
• Fault tolerance is an inherent property of swarm intelligence systems due to the decentralized, self-organized nature of their control structures. Because the system is composed of many interchangeable individuals and none of them is in charge of controlling the overall system behavior, a failing individual can be easily dismissed and substituted by another one that is fully functioning.

Journal of Swarm Intelligence and Evolutionary Computation provides an International forum for the publication of papers in the following areas. Artificial Intelligence; Robotics; Modelling & Analysis of swarm particle optimization; Swarm Intelligence; Evolutionary programming & Evolutionary Genetics; Genetic Algorithm & Genetic Programming; Ant colony Optimization; Bacterial Forging; Artificial Life & Digital Organisms; Bioinformatics; Evolutionary Computation; Artificial Immune System; Computing; Nano computing; Computational intelligence, etc. Swarm Intelligence journals are at higher echelons that enhance the intelligence and information dissemination on topics closely related to Swarm Intelligence. Computational methods in synthetic biology play a major role in this journal.

You can submit your related manuscript to www.longdom.org/submissions/international-swarm-intelligence-evolutionary-computation.html for publication in any type of research work as original papers, review article, and short communication.