Swarm Intelligence beyond Stigmergy: Traffic Optimization in Ants

Swarm intelligence is widely recognized as a powerful paradigm of self-organized optimization. Whereas the stigmergy concept of information exchange has revealed a vast body of successful applications in distributed artificial intelligence, the role of physical interactions in swarm intelligence was explored only recently. Here we show that physical encounters in ant traffic play a vital role in the optimization of transport processes in ant colonies, if the capacities of transport ways are limited. In crowded situations ant traffic is optimized through a balanced interaction of pheromone guided trail following behavior and a congestion driven rerouting of ants. This points towards a promising design-principle for self-optimizing artificial transport systems.