How stock trading is like a traffic jam
In the world of technology we can see similar system behavior -- often called multiple agent systems or MAS -- in the fluctuations of the stock market or the formation of traffic jams. We have made use of these principles in a wide variety of applications to move information, in routing data packets in telecommunications, to move material in designing delivery or repair routes, and to move energy in optimizing power grids. Internet searches, customer preferences, and market predictions have all been enhanced by the use of these “bottom up” simulation models.
Southwest Airlines has used an ant foraging model to design a gate assignment system. Each plane "remembers" the gates with the shortest delays and queues accordingly.
Regen Energy of Toronto manufactures an autonomous wireless power controller for the household that minimizes peak electricity demand and communicates with other units to do so. Icosystem of Cambridge, Massachusetts has organized field crews for more efficient gas and oil drilling using an "evolutionary computation" based on insect foraging.
Our current highway system is a basic example of the kind of system in which these agent-based algorithm principles could be applied. Changing the timing and spacing of cars on the road, without even touching their power systems, could result in a 33 percent improvement in efficiency for urban drivers, according to estimates. That's better than the 20 percent gain we could get from converting gasoline-powered cars to hybrids. A relatively cheap sensor system would be employed to create telematics-enabled vehicles.