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can a neural network learn to walk as a physical object in a physics simulation? here I train walking neural nets with an evolutionary algorithm. The input nodes/feet are activated by sine waves at learned phases & connections between two neurons extend based on their difference

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Matt Henderson

80,126 subscribers

339,220 Aufrufe • vor 3 Jahren •via X (Twitter)

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10 Kommentare

Profilbild von Matt Henderson
Matt Hendersonvor 3 Jahren

aka “embodied neural networks”

Profilbild von Matt Henderson
Matt Hendersonvor 3 Jahren

Remember soda constructor?

Profilbild von Patrick Ꝺoyle
Patrick Ꝺoylevor 3 Jahren

Whatever the result, they seem to be enjoying themselves.

Profilbild von Eric Jang
Eric Jangvor 3 Jahren

this is amazing. would you consider open-sourcing the code? I'd love to extend this to optimizing the architecture of the net itself, so it ends up having to trade off physical bulk with function approximation power

Profilbild von Tom
Tomvor 3 Jahren

Looks kinda similar

Profilbild von Austen Lamacraft
Austen Lamacraftvor 3 Jahren

Surely a CNN will work better because of the strides?

Profilbild von c7ddfc
c7ddfcvor 3 Jahren

reminds me of this, also controlled by a neural net

Profilbild von Mike Vella
Mike Vellavor 3 Jahren

How do you think of this stuff??

Profilbild von Matt Henderson
Matt Hendersonvor 3 Jahren

I saw a cool demo of a neural net controlling an inverted pendulum, and was thinking it would be cool to make a nnet control something. I was also thinking about that old game soda constructor. Then I thought of this idea like a bad joke about learning to walk

Profilbild von Connor McCormick
Connor McCormickvor 3 Jahren

You should make it so that the ground is a treadmill with numbers on it, and the fitness function rewards it both for walking and for adding the numbers it's touching correctly.

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