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Erschienen in:
2016 | OriginalPaper | Buchkapitel
1. Complexity and Swarming Systems
verfasst von : Roland Bouffanais
Erschienen in: Design and Control of Swarm Dynamics
Verlag: Springer Singapore
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Abstract
Complexity science has shown that collective behaviors in animal groups, that is swarms, emerge from repeated local interactions between neighboring individuals. It has also revealed that a set of simple local interaction rules applied to very simple artificial agents gives rise to complex patterns possessing long-range and long-lasting dynamic order. These swarming systems, be them natural or artificial, are all characterized by somehow similar features: (i) lack of central controller or leader overseeing the collective dynamics, instead the latter emerges through self-organization, (ii) local perception of the environment leading to a certain level of global knowledge by means of effective distributed information sharing, and (iii) a high degree of adaptation to rapidly changing circumstances. These features afford swarms unique distributed problem solving capabilities—a.k.a. swarm intelligence—such that collectively they perform tasks far exceeding each individual agent’s ability.