Decoding the Remarkable Algorithms of Ants
Ants in particular excel at collective search, automatically tailoring their search strategy to efficiently cover large areas of ground. Gordon has found parallels between the algorithms ant colonies use for foraging and the man-made ones that underlie the Internet. Given how long ants have been solving these kinds of problems, Gordon hopes that she will uncover new algorithms that will ultimately make large-scale computing networks cheaper and more efficient.
What has most impressed you about ants?
I’m impressed by the contrast between the coordinated responses of colonies and the ineffective and incomplete actions of individual ants. In other words, colonies accomplish a lot, but no ant is very competent on its own.
.. For harvester ants, we’ve learned that an ant decides whether to go out of the nest and forage using the rate at which it meets ants coming in with food. It’s a form of positive feedback; the faster ants are coming in with food, the more ants go out. Each ant decides only when its rate of interaction is high enough to go out. Overall this system allows the colony to regulate foraging activity so that the ants don’t go out unless there’s enough food to make it worthwhile.
.. In some ways they have sacrificed what we think of as efficiency for resiliency.
.. Rather than sending one really complex robot to explore Mars or to search a burning building, it makes sense to send a group of cheap robots that will still work as a group even if one malfunctions.