Swarm intelligence (SI) is a field of study that seeks to understand and modelcollective behaviors observed in natural social systems, such as ant colonies, beehives, termite mounds, flocks of birds or schools of fish. The central principleof SI is that complex intelligent behaviors can emerge from the interactions of large numbers of simple individual entities, without any centralized controlor monitoring. SI researchers aim to uncover the underlying principles and mechanisms behind this SI, with the aim of applying these concepts to solve complex problems in areas such as optimization, robotics, transport, IT, etc. As the field continues to evolve, SI is expected to have an increasingly significant impact on our understanding of biological systems and our ability to design intelligent systems capable of adapting and thriving in complex environments and dynamic. This article aims to introduce the reader to the field of SI, presenting its fundamental concepts, key principles, existing applications, and prospective future developments.
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