Swarm intelligence is the collective, self-organized and seemingly intelligent behavior of a large number of simple individuals interacting locally with each other and with their environment. Without any central control structure, such local interactions lead to a complex global behavior. Swarms of insects, fish or birds are the classical examples in biology.
In the physics of complex systems, similar phenomena occur in the context of critical behaviour, such as when water freezes or iron becomes magnetic. Here the guiding principles are self-organization, symmetry breaking and percolation, and these have led to a well-developed formalism; it identifies universality classes of phenomena differing in detail, but sharing crucial critical structures.
In mathematics and informatics, the theory of graphs and networks has provided a common structural framework which can be applied to the phenomena of biology as well as to those of physics. This has led in the past twenty years to a new challenging interdisciplinary field of research. In the more recent past, two developments (among others) have led to considerable progress. A large project (‘Eurostar’) has made use of high speed photographic technology combined with modern computer-based analysis methods to provide for the first time reliable data of the structure and organization of bird swarms. In this context examples to mention are the lectures given by Alessio Cimarelli, Guy Theraulaz and Charlotte Hemelrijk. They presented biological and simulation results describing the flocking behavior of fishes and birds. With respect to the latter, particularly impressive observations of flocking starlings have been shown. Interestingly, the complex behavior of these animals could be simulated by essentially applying three simple rules. Applied are potential functions to avoid too small and too large distances to the neighbors. Animals take into account the five to seven next neighbors, independent of the absolute distances.
On the other hand, self organization models from statistical physics now allow a mathematical modelling of bird swarm behavior. It therefore seemed timely to bring together experts from the different areas of this interdisciplinary field to discuss and summarize common structures and their understanding.
Frank Brand (Berlin), Alessio Cimarelli (Rom), Romain Clément (Berlin), Andreas Deutsch (Dresden), Andreas Dress (Bielefeld), Raghavendra Gadagkar (Bangalore), José Halloy (Brüssel), Charlotte K. Hemelrijk (Groningen), Max-Olivier Hongler (Lausanne), Ani Hsieh (Philadelphia, PA), Serge Kernbach (Stuttgart), Jens Krause (Berlin), Alcherio Martinoli (Lausanne), Martin Middendorf (Leipzig), Helge Ritter (Bielefeld), Julio Rodriguez (Lausanne), Madeleine Sirugue-Collin (Marseille), Guy Theraulaz (Toulouse), Richard L.C. Vink (Göttingen), Martin Weigel (Mainz)