tokens: Reinforcement Learning ( RL ) has been able to deal with big state spaces , including states derived from pixel images in Atari games , but the learning is slow , depends on the brute force mapping from the global state to the action values ( Q - function ) , thus its performance is severely affected by the dimensionality of the state and can not be transferred to other games or other parts of the same game .