say I want to see if i can get a biped to walk upright with an ANN.
I have a fitness function, and how I plan on adjusting weights is for
each output, i test random deviations of the output with the fitness
function till i achieve a better result (just ever so slightly just for
the next frame), then i back propagate this…
would this work?
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Have a look here
Can’t find the original video at the moment where they start with a
single legged creature and used GA to get it to hop around.
Then they did a biped
wow i must say that truly is amazing, and just to think, it all came
from a little laboratory back in 1957 with the first perceptron!
Euphoria is an amazing achievement, but the animations looks just like
marionettes. The puppeteering engine needs to be way more proactive to
look natural. The most convincing parts were the falling and stumbling,
situations where a human would be caught off guard and only
instinctively controlling their movement.
The other product they do handles that.
You create networks of animations and it blends between them based on
Ah. The video gave me the impression it was a complete character
I want to take this idea further!!! Id like a wrestling game or
something (take ragdoll gaming to the next level) - it would be really
But setting up the physics system and neural net learning is really
oh well, i guess god wanted it to be a challenge anyway…
The system mixes generated animations and artist created animations
based on events.
It’s power comes from the fact that it can blend multiple animations in
a realistic way.
The stuff that really makes a difference is the reaction system, for
example someone getting shot. Traditionally we have one or two death
animations, but with their system it actually has almost an infinite set
of reactions depending on the nature of the event.
Makes a big difference.