<P>Swarm Intelligence (SI) is a computational intelligence technique involving the study of collective behavior in decentralized systems. Such systems are made up by a population of simple individuals interacting locally with one another and with their environment. Although there is typically no centralized control dictating the behavior of the individuals, local interactions among individuals often cause a global pattern to emerge. Examples of systems like this can be found in nature, including ant colonies, animal herding, bacteria foraging, bird flocking, fish schooling, honey bees, and many more. </P> <P> <B>Keywords:</B></P> <LI>Modeling and analysis of particle swarm optimization, Ant colony optimization, culture algorithm, foraging algorithm. <LI>Optimization techniques in dynamic, multi–objective, constrained environment. <LI>Modeling and analysis of biological collective systems such as social insects colonies, school and flocking vertebrates. <LI>Distributed computing, machine learning, data mining, data clustering, graph partitioning, and decision making based on swarm intelligence principles. <LI>Theory and applications of swarm intelligence principles to real world problems including control systems, evolvable hardware, power system, sensor networks, bioinformatics, business and finance, supply–chain management, planning and operations in industrial systems, transportation systems, and others areas<BR></LI>
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Louis
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United States
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