Getting the Google DeepMind Atari action into the snake game. More Videos follow…
Basically this algorithm learns a strategy to succed in a Game without any prior domain knowledge. The Agent perceives its environment and gets rewards/punishments after each action. When starting the algorithm the agent makes random movements and slowly learns from its mistakes converging to perfect policy.
Performs perfect on its environment, but needs very long for training calculation.
Policy Gradient (linear)
gives most promising result, but fails stupid and hard