Takeaway: Seemingly Intelligent behavior does not always mean that the decision process was complex.
For example, mechanical wind-up toys can avoid falling off an edge simply by using a fly-wheel that rotates at a right angle to their direction of motion and a caster wheel. Once the caster wheel loses contact with the ground—that is, when the robot has reached the edge—the fly-wheel kicks in and pulls the robot to the right
You can do this with a more complex methodology.
Ants find the shortest path because the shortest path builds up pheromones more rapidly and the ants simply follow that to find food. Sometimes, their pheromone sensing is faulty and they end up exploring and finding new food.
Every now and then, ants give the longer path another shot, eventually finding new food source. What looks like intelligent behavior at the swarm level, is essentially achieved by a pheromone sensor that occasionally fails. A modern industrial robot would solve the problem completely differently: it would first acquire some representation of the environment in the form of a map populated with obstacles, and then plan a path using an algorithm