A long time ago, people discovered the variety of the interesting insect or animal behaviors in nature. A flock of birds sweeps across the sky. A group of ants forages for food. A school of sh swims, turns, as together, etc.. We call this kind of aggregate motion \swarm behavior.” Recently biologists and computer scientists in the eld of \articial life” have studied how to model biological swarms to understand how such \social animals” interact, achieve goals, and evolve. Moreover, engineers are increasingly interested in this kind of swarm behavior since the resulting \swarm intelligence” can be applied in optimization (e.g. in telecommunicate systems) , robotics [3, 4], trac patterns in transportation systems, and military applications .
Research Professor. Director at Learning Change Project – Research on society, culture, art, neuroscience, cognition, critical thinking, intelligence, creativity, autopoiesis, self-organization, rhizomes, complexity, systems, networks, sustainability, thinkers, ++
Giorgio Bertini does not work for, consult, own shares in or receive funding from any company or organization that would benefit from these papers, and has disclosed no relevant affiliations beyond their academic appointment.
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