Insects, on the other hand, despite their tiny, poppy-seed-sized brains, have a perhaps surprising amount of wisdom when it comes to decision-making. Many insect problem-solving skills have, in fact, inspired algorithms for efficient deliberation in real-world human industries.
Here are five things we can learn from bugs about making wise choices.
Optimising ants
Making your mind up on the best way to get something done is no easy task – especially in a world with so much stimuli. It’s called choice overload.
Ants, too, are faced with such a conundrum when they are making a group decision about their next foraging spot. But they’ve evolved a neat trick, common across a variety of different species.
At first, several ants leave the comfort of their nest, questing to find the closest and best place for a hearty meal. The adventurous ants go out into the wild at random, keeping all their options open and exploring different paths. Along the way and back, they leave a faint pheromone trail on the ground for other ants to follow later on. These pheromones evaporate over time, and ants are more likely to follow the strongest trail.
The ants that find the most efficient foraging spot get back faster with the food, and trace over their pheromone trail before it evaporates completely. They also pass the relay more quickly to any following ants going out to forage. This means that over time, more ants tend to go back and forth along that path, leaving more cumulative pheromone, making the trail smell stronger.
The objectively shorter pathways are therefore reinforced over time, while the others fade away. In the end, the colony collectively finds the shortest and most efficient path without any one ant specifically knowing it was theirs.
“The main lesson… is that efficient collective decision-making can emerge without centralized control,” says Marco Dorigo, co-director of the artificial intelligence lab of the Université Libre de Bruxelles, in Belgium. “[Ants are] simple individuals with limited capabilities and only local information, yet they are able to collectively solve complex coordination problems.”
