Ant colony optimization algorithms describe probabilistic techniques for solving computational problems by modeling the behavior of ants following one another's pheromone trails.
Ant colony optimization algorithms describe probabilistic techniques for solving computational problems by modeling the behavior of ants following one another's pheromone trails (leading between their nest and food sources).
They are use for finding optimal paths in graphs and are similar to simulated annealing algorithms).