The basic searching behaviors, more kind of this emergent property, we're able to copy the way that ants do that. And so at that point, the transport part of the swarm is still autonomous. The robots aren't there's no central controller right the robots get to a particular place they have a particular behavior that they use. We had to impose this hierarchy of movement in simulation we imagined and we actually built dump trucks. But it's not that sort of, you know, truly adaptive behavior that would, but that we had with our original swarm.
Imagine you were going to Mars with a swarm of robots, and you needed to send those robots out foraging. How would you program them? A traditional top-down approach to programming would mean programming what every single robot is going to do, and that's going to get complicated fast.
So in this episode, we're joined by Melanie Moses, Professor of Computer Science at the University of New Mexico, and External Faculty at the Santa Fe Institute. Melanie is going to explain how you can take lessons from complexity science, and utilise a bottom-up approach to programming a swarm. In other words, she's going to explain how you can program the robots to interact with one another. And if you thought you'd heard the end of scaling or power laws, then you're in for a surprise, because Melanie is going to share how scaling fits in with her work on getting robots to work as a team.
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