1. A method for intelligent multi-scale image parsing, the method comprising: specifying, by a processor, a state space of an artificial agent for discrete portions of a training image, the state space specified by a parametric space and a scale space for the discrete portions of the training image; determining, by the processor, a set of actions, the set of actions comprising parametric actions specifying a possible change in the parametric space with respect to the training image and scale actions specifying a possible change in the scale space with respect to the training image; establishing, by the processor, a reward system based on applying each action of the set of actions and based on at least one target location of the training image; and learning, by the processor, an optimal action-value function approximator of the artificial agent specifying the behavior of the artificial agent to maximize a cumulative future reward value of the reward system, wherein the behavior of the artificial agent is a sequence of actions moving the agent towards the at least one target location of the training image, the sequence of actions comprising at least one scale action.