Hi all,
For some reason I couldn’t find this post one hour ago and so I made a new topic: sorry about that.
Anyway, here’s the thing: I am researcher in AI and a PP backer, though I cannot play the pre-alpha yet as I am using a Mac.
While reading this post and hearing of bell curves and the likes, I got nerd-sniped 
It took some time, but I think I may have worked our most of the theory behind bullet trajectory generation, and as a plus I found a way to control the sampling so that the resulting probabilities follow a highly customizable and (hopefully) widely acceptable pattern.
I probably ended up reinventing the wheel (the devs are likely doing something similar), but in the off-chance that I found something new I’ve set up a small git repository and a (long-ish) post in html and pdf format which explains the goal and the process.
Long story short:
- High probability values should appear close to the center of the circle…
- …But when you need to generate trajectories, it’s important to make use a roughly bell-shaped distribution
Plus: knowing the theory means that the process can be tightly controlled to reach exactly the desired results.
The full post can be displayed via gitpreview
You can also get the pdf from the repository (the links in the document won’t work unless you download the file though, due to limitations in github pdf viewer – they are not particularly important, though).
Cheers,
Michele