Path efficiency of ant foraging trails in an artificial network.

In this paper we present an individual-based model describing the foraging behavior of ants moving in an artificial network of tunnels in which several interconnected paths can be used to reach a single food source. Ants lay a trail pheromone while moving in the network and this pheromone acts as a system of mass recruitment that attracts other ants in the network. The rules implemented in the model are based on measures of the decisions taken by ants at tunnel bifurcations during real experiments. The collective choice of the ants is estimated by measuring their probability to take a given path in the network. Overall, we found a good agreement between the results of the simulations and those of the experiments, showing that simple behavioral rules can lead ants to find the shortest paths in the network. The match between the experiments and the model, however, was better for nestbound than for outbound ants. A sensitivity study of the model suggests that the bias observed in the choice of the ants at asymmetrical bifurcations is a key behavior to reproduce the collective choice observed in the experiments.