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What? Handbook About Home |
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What?
Imagine that it is the year 2091 and your moon-Jeep is being repaired
by a swarm of microscopic machines to fix some serious moondust
damage. Do you trust them to do the job right?
Now, imagine that it is the
year 2061 and the city of New York launches a new surveillance system
consisting of a swarm of autonomic microflyers. Do you feel secure?
Imagine that it is the year 2031 and there is the first android team
that challenges a human soccer team for the ceremonial opening game at
the world soccer championships. Which team do you put your money on?
These future scenarios have one common denominator: they all involve complex systems consisting of (many) interacting parts that are self organising and collectively intelligent. Simulation of Collective Intelligence is about the understanding of the behavior and self-organization of complex systems: systems in which the interaction of the components is not simply reducible to the properties of the components. The general question of interest is: how should systems of very many independent computational (e.g., robotic or software) agents cooperate in order to process information and achieve their goals, in a way that is efficient, self-optimising, adaptive, and robust in the face of damage or attack? Therefore we look at natural systems that solve some of the same problems that we want to solve, e.g., adaptive path minimization by ants, wasp and termite nest building, army ant raiding, fish schooling and bird flocking, coordinated cooperation in slime molds, synchronized firefly flashing, evolution by natural selection, game theory and the evolution of cooperation. |