Earlier quoted context omitted.
> I wonder if any fighting games have thought to train a neural network per player to try and predict the player's actions N frames ahead. The entire point of playing a fighting game is to attempt to solve this problem. A good player, by necessity, can't be accurately predicted; if they could, they'd be a bad player.
There's only a few key moments where players need to be unpredictable to win a game. Almost all the rest of the time they are executing predictable consequences of those unpredictable choices. ie: imagine a player running to a ledge spanning a gap. The "naive" interpolation would be they continue running and fall off the ledge and die. A smarter system would realize that almost all the times they've run to the edge o…
I assume the interpolation relates to something displayed on the screen? The idea makes me kind of uncomfortable, because it seems like it would confuse players by causing identical jumps to display different results. If you only learn about jumping by watching the departure point and the landing point, fine, but if part of how you get used to jumping is by watching the animation, this sounds like it could make things a lot harder.
(If the player sees position data calculated locally, and the interpolation is just a process for bringing the remote idea of where the player is into line with the local idea of where he is, that sounds much better.)