Radix Octrees

As I understand, they can be used to predict the next state of a system: think using them with Markov Chains.

I.e. we use markov chain on every pixel, then integrate the state to then next octree level, calculate again, and so on, till we reach tree root, having the folded prediction.

Say you write an AI for an RTS game. The current game map contains AI player base with enemy units near it. AI has memory from previous plays, which got him octree that enemy units near his base with have high probability following attack on it's base, which would trigger other octree, having memory that moving his AI's own units near base, would efficiently counter the attack. And so AI does that.

Basically you can use Radix Octrees with some "glue" code to completely encode AI behaviour.

>>4

Are you really thinking of using raw pixel planes as input, or was that just a (very bad) example?

AFAIK, animal brain does some filtering, like edge detection and feature extraction, before starting pattern matching. But in our case of a chess-like video game with rock-paper-scissors mechanics we can simplify processing by using pixels, say red pixel for enemy unit, green for friendly, and blue for base.

Because that's retarded. That's like learning to read by studying the molecular makeup of ink.

Octrees would aggregate your "ink" into letters and letters into words. So molecules of ink, like a red point (enemy unit) few pixels away from a base (blue point), would end up being letters (a state), which could be into a markov chain or a radix tree to get prediction/response.