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Yes, Ants Think — Like Computers

Denyse O'Leary
Photo: Leafcutter ants, by Pjt56, CC BY-SA 4.0 , via Wikimedia Commons.

Navigation expert Eric Cassell, whose recent book is Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts, offers some insights into how ants organize themselves by using what amount to algorithms, without any central command:

Ants are remarkably consistent in their lifestyle. All of the roughly 11,000 species of ants live in groups, large or small. There are no known solitary ants. 

Living in groups, they have developed a social lifestyle that includes “agriculture, territorial wars, slavery, division of labor, castes, consensus-building, cities, and a symbolic language.” (p. 85) How is this managed by ants with very small brains (200,000 to 250,000 neurons) and very limited individuality?

For comparison, among mammals, the agouti has roughly 857 million neurons, the capybara has 1.60 billion, and the capuchin monkey, 3.690 billion. Humans have roughly 85 billion neurons. It seems that the ant is doing something that does not rely on individual problem-solving skills.

Cassell points out that the ants’ complex colony organization where one queen or several queens lay all the eggs and the other females do all the work is almost exclusively the domain of life forms with very small brains. The naked mole rat is the only mammal that follows this pattern. Incidentally, the naked mole rat has fewer neurons in a smaller brain than expected for its body size, relative to other rodents.

Such colonies are sometimes called “superorganisms” because the individual organisms work for the survival of the colony as a whole. Take these leafcutter ants in Brazil:

What Are Some of the Ant Colony’s Methods?

We don’t know exactly how the ant “algorithm” works out divisions of labor but one study found that young ants typically tend to the eggs, larvae, and pupae while older ants forage outside the nest. Foraging is a much more dangerous activity than tending the young, so if the older ants forage, fewer days of ant life are lost to the colony (pp. 89–90). Some ant species have castes of workers with specially shaped heads, best suited to specific purposes like attacking other ants or blocking a tunnel (pp. 95–96). In that case, they might naturally gravitate to the task without having to think about it. They just find it easier than the differently structured ants would.

Ants communicate mainly by pheromones, scents that provide information. In their book The Superorganism: The Beauty, Elegance, and Strangeness of Insect Societies (2008), Bert Hölldobler and E. O. Wilson (1929–2021) identified 12 areas of communication mediated by pheromones, including “alarm, attraction, recruitment, grooming, feeding, exchange of fluids and solid particles, group effect, recognition of nestmates, caste determination, control of other individuals competing for reproduction, territoriality, and sexual communication” (p. 90).

What makes pheromones a complex communication system is that most emissions are of several pheromones mingled rather than only one. Some signals are recognized by all ants in the vicinity, others only by the ant’s own species, and others are specific to the ant’s colony. 

One evolutionary biologist describes the processing of pheromones as equivalent to AND gates and STOP in a computer system. (p. 91). The ant is not so much deciding what to do as responding to an AI-like signal.

Computer programmers have adapted ant algorithms to the computer:

Welcome to the Anternet!

Stanford’s Deborah M. Gordon, a specialist in ant behavior, thinks of the complex algorithms ants use to communicate without personal understanding as the “anternet”:

Ant colonies use dynamic networks of brief interactions to adjust to changing conditions. No individual ant knows what’s going on. Each ant just keeps track of its recent experience meeting other ants, either in one-on-one encounters when ants touch antennae, or when an ant encounters a chemical deposited by another.


Read the rest at Mind Matters News, published by Discovery Institute’s Bradley Center for Natural and Artificial Intelligence.