Robots can make decisions based on the density of things around them. This is because pheromones going to big piles start to decay, they evaporate over time. So this sort of natural tendency then of positive feedback when something stays sort of good,. It's a big dense pile of food, and decay as that isn't reinforced leads to the ability for the swarm to have a map of their environment.
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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