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Swarm Intelligence: Where We’ve Been and Where We’re Going
Russell C. Eberhart, Ph.D.
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Abstract The definition of, and basic principles of, swarm intelligence are first discussed. Application areas are listed. Three swarm intelligence paradigm examples are reviewed: cultural algorithms, ant colony optimization, and particle swarm optimization. Tracking and optimizing dynamic systems with swarms is discussed. Two recent applications are summarized: unmanned air vehicle mission planning, and putting a person in the swarm using an NK landscape game. Measuring swarm population diversity, and using non-parametric statistics for performance metrics are reviewed. Finally, recent accomplishments of the swarm intelligence field, and challenges being faced by the field, are outlined |