Analysis of foraging behavior in ant swarms based on Starlogo simulation

Swarm Intelligence which is inspired by social animals has gained a lot of attention recently. It always appeals to the collective behaviors observed in social animals. Foraging behavior in ant colonies have come to be viewed as a prototypical example of how complex group behavior can arise from simple individuals. In this paper, foraging process with two sources observed in ant system is simulated by Starlogo. Three aspects, the distances of sources, the evaporation speed of the pheromone, the number of individuals, are considered respectively. Each individual is controlled by the Finite State machine. The completion time is the estimation standard of system performance. The results of simulations show the power law relationship between the completion time (also collision frequency) and the flux of foragers. The work presented here guides a better understanding on self-organization and Swarm Intelligence. It can be used to design more efficient, adaptive, reliable intelligent systems.