Applications of Swarm Intelligence (original) (raw)
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International Journal of Advanced Research in Computer Science and Software Engineering
Swarm intelligence is the emergent collective intelligence of groups of simple agents. It belongs to the emerging field of bio-inspired soft computing. It is inspired from the biological entities such as birds, fish, ants, wasps, termites, and bees. Bio-inspired computation is a field of study that is closely related to artificial intelligence. This paper provides a brief introduction to swarm intelligence.
Biological Foundations of Swarm Intelligence
Why should a book on swarm intelligence start with a chapter on biology? Because swarm intelligence is biology. For millions of years many biological systems have solved complex problems by sharing information with group members. By carefully studying the underlying individual behaviours and combining behavioral observations with mathematical or simulation modeling we are now able to understand the underlying mechanisms of collective behavior in biological systems.
Swarm Intelligence and Its Applications
The Scientific World Journal, 2013
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. SI systems are typically made up of a population of simple agents 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. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling. Research in SI started in the late 1980s. Besides the applications to conventional optimization problems, SI can be employed in library materials acquisition, communications, medical dataset classification, dynamic control, heating system planning, moving objects tracking, and prediction. Indeed, SI can be applied to a variety of fields in fundamental research, engineering, industries, and social sciences. The main objective of this special issue is to provide the readers with a collection of high quality research articles that address the broad challenges in application aspects of swarm intelligence and reflect the emerging trends in state-of-the-art algorithms. The special issue received 42 high quality submissions from different countries all over the world. All submitted papers followed the same standard (peer-reviewed by at least three independent reviewers) as applied to regular submissions to "this journal". Due to the limited space, 15 papers
Book: Theory and New Applications of Swarm Intelligence
2012
The field of research that studies the emergent collective intelligence of self-organized and decentralized simple agents is referred to as Swarm Intelligence. It is based on social behavior that can be observed in nature, such as flocks of birds, fish schools and bee hives, where a number of individuals with limited capabilities are able to come to intelligent solutions for complex problems. The computer science community have already learned about the importance of emergent behaviors for complex problem solving. Hence, this book presents some recent advances on Swarm Intelligence, specially on new swarm-based optimization methods and hybrid algorithms for several applications. The content of this book allows the reader to know more both theoretical and technical aspects and applications of Swarm Intelligence.