I was having issues with tables persisting when I thought they should have been deconstructed. That's sorted out now...

The only problem I have now is that it appears as though I'm having random collisions... as if the shapes are at a different location than the body/sprite.

No idea.

Ah, I see that now.

On a further note, LUA garbage collection/object persistence is freakin crazy.

Well, I don't really know what Bartbes is, let alone 2.0, but I'm just going for a simple Neural Network and genetic algorithm.

I'll release the source code when I'm satisfied, but it's mostly just for learning/fun.

Oh wow, that was quite revealing.

Each neuron was only supposed to have 4 weights... but apparently it had 4080 o.O

Wonder what the hell was causing that...

Well, time to debug that. Thanks for the trick!

hehe... oopsie. I see

Well, lemme give that a try. I was just using default config. Could you enable the console in 0.5?

You're welcome

I tried printing, but Love doesn't return to the draw function until that function has finished executing, so I get no output. I tested that this function was what was causing the crash by commenting everything else and having love.update only call this function. No function call, no crash. As for m...

I don't really understand what you're saying. Use a sprite (love.graphics.newImage) and simply have it over the location of the body.. The image itself has nothing to do with love.physics apart from making sure they align. Now, if it looks bad when it's rotated, that's an entirely different problem.

I asked almost this exact same question about a month ago and the short answer is that you cannot do this. If you're like me and you thought about using the particle system for shoot em up bullets, then the solution is to make an object for each bullet and track each bullet individually. It's really...

I'm trying to flatten some nested tables. Well, I'm actually not flatting nested tables, just extracting the data from the innermost nested table into a flat table. The code in question is: function NeuralNetwork:GetWeights() -- Initialize Empty Weights Table Weights = {} -- Iterate Layers, Then Neu...