Learning robot control

Learning is essential to expand the capabilities of a robot. But what is the meaning of learning for a robot and how is the implementation of a learning task? This question is a key question and in addition to what should be learned. This paper defines a general learning model, classify robot learning and develops a learning architecture for locomotion of a simple walker. These learning architecture contains a construction of the simple walker, the Q-Learning algorithm, the development of an appropriate reward function and consider the convergence of the learning system.