Comment on Neural BoidsComments−adammarples6moWhat's the point of training a nnet on outputs from the original 3 rules so it can effectively just relearn them?−kjshsh1236moKinda agree. Training the network with RL instead and penalizing collisions and rewarding collecting something like food would be interesting.As long as the birds can't change direction too quickly (e.g. output acceleration, not velocity) I'd guess you get flocking.−daemonologist6moI agree that this would be a more interesting approach; I think you might need more incentives to create a flock though (aerodynamic benefits, predator protection, etc.)−ectoOP6moAwesome idea!−jayGlow6mobased on the article the noida approach has better performance and is able to run on a GPU while the Sterling implementation must run on a cpu.−adammarples5moPotentially though there's nothing stopping someone from writing the original three rules using cuda−ectoOP6moWhat happens when you want to simulate millions of rules?What if they weren't noids?−brcmthrowaway6moYeah, this is well presented slop.−ectoOP6moThanks!
Comments
What's the point of training a nnet on outputs from the original 3 rules so it can effectively just relearn them?
Kinda agree. Training the network with RL instead and penalizing collisions and rewarding collecting something like food would be interesting.
As long as the birds can't change direction too quickly (e.g. output acceleration, not velocity) I'd guess you get flocking.
I agree that this would be a more interesting approach; I think you might need more incentives to create a flock though (aerodynamic benefits, predator protection, etc.)
Awesome idea!
based on the article the noida approach has better performance and is able to run on a GPU while the Sterling implementation must run on a cpu.
Potentially though there's nothing stopping someone from writing the original three rules using cuda
What happens when you want to simulate millions of rules?
What if they weren't noids?
Yeah, this is well presented slop.
Thanks!