Drawing heavily on the chemistry of biology, researchers from Humboldt University in Germany have devised a way for electronic agents to efficiently assemble a network without relying on a central plan.
The researchers modeled their idea on the methods of insects and other life forms whose communications lack central planning, but who manage to form networks when individuals secrete and respond to chemical trails.
The researchers found that what works for ants and bacteria also works for autonomous pieces of computer code. “The idea is inspired by chemotactic models of tracking trail formation widely found in insects, bacteria, [and] slime molds,” said Frank Schweitzer, an associate professor at Humboldt University and a research associate at the Fraunhofer Institute for Autonomous Intelligence Systems in Germany.
The work could eventually be used for self-assembling circuits, groups of coordinated robots and adaptive cancer treatments, according to Schweitzer.
Insect, bacteria and slime mold communities coordinate growth processes based on interactions among chemical trails left behind by individuals. The researchers set up a similar network using a computer simulation of electronic agents moving randomly across a grid containing unconnected network nodes.
Rather than determine the structure of a network in a top-down approach of hierarchical planning, agents found nodes and created connections in a bottom-up process of self-organization.
When an agent happened on a node, it began to produce one of two simulated chemical trails at a rate that decreased in time. The strength of the chemical trail also faded as time went by. The key to the self-assembling network is that the agents are drawn to the chemical trails laid down by other agents.
The researchers’ model contains two types of network nodes-blue and red. Each agent starts out as a green agent, which lays down no chemical trails and travels randomly. When an agent happens on a blue node, it turns blue, and when an agent happens across a red node, it turns red. Red and blue agents lay down chemical trails that attract agents of the opposite color.
Over time the model changes from many green agents traveling randomly to colored agents moving among nodes like traffic in a network. “You see a network that connects almost all neighboring nodes,” said Schweitzer.
The chemical method simultaneously solves the two basic problems of network self-assembly-detecting nodes and establishing links between nodes, Schweitzer said.
This type of network quickly addresses failures and disturbances, said Schweitzer. “If the position of the nodes is changed, the network adjusts accordingly. If a link is broken, it will be restored very fast.”
The results should assist efforts to use virtual pheromones to coordinate computer agents and real-world robots, said Schweitzer. Pheromones are the chemicals used by ants in their networks. The same principles can be used to develop self-assembling electronic circuits from building blocks like nanowires, he said.
Self-assembling networks are important, said Tamas Vicsek, a physics professor at Eotvos University in Hungary. “In fact, networks like the Internet are being assembled continuously based on their actual performance,” he said.
Viksek said the Humboldt researchers’ model could provoke useful insights for those who run networks. While other network designs also change their structures as a function of time and other parameters, the Humboldt team set their model apart by introducing agents-a nice touch, according to Viksek. But, he added, the model is currently too complicated to be widely applied.
“This is a direction which is worth developing further,” he said.
Schweitzer’s research colleagues were Sankt Augustin and Benno Tilch of Humboldt University. They published the research in the August 21, 2002 issue of Physical Review E. The research was funded by Humboldt University.
Become an MIT Technology Review Insider for in-depth analysis and unparalleled perspective.Subscribe today