> But we had made it so much more complicated because we couldn’t see the few simple rules that each of them were following.

I hope you don't mean "Boids" and the three-four simple rules, because that's just an approximation of a swarm behavior made for artistic purposes - i.e. the result is supposed to pass as a flock of birds or a school of fish to casual onlookers (e.g. gamers, audience of a movie), and not to be accurate to the real thing.

Here's a project from 1998 where a Boids-like model was used for engineering purposes. A robot controller was designed to guide a simulated flock to a goal on the edge of a circular arena. The robot worked on real flocking ducks too, on the first try. The Boids sim was similar enough to the birds' behavior in this very limited domain to be used as an engineering sim.

'Robot Sheepdog' : https://www.youtube.com/watch?v=tefXVXscNDM

Even if it were "Boids", I don't think it worsens the argument by a lot. The essence of the statement is that complex behavior can emerge from a simple ruleset.

I'd like to add, that while individual behavior is difficult to predict, a general motion prediction can be much easier. (Think shepherds, for example)

All the complexity in farming is in getting the view on the small fraction of the area and applying treatment (water, fertilizer, removing weeds etc) into that area.

The "swarm" is meaningless there. Each node need to have minimum amount of sensing and computation to handle that job.

It's also at worst "a sloped square" so there is no "swarm mechanic" to move around, just zigzag around the field.