Machine learning for autonomous robots

Abstract

Although Reinforcement Learning methods have meanwhile been successfully applied to a wide range of different application scenarios, there is still a lack of methods that would allow the direct application of reinforcement learning to real systems. The key capability of such learning systems is the efficency with respect to the number of interactions with the real system. Several examples are given that illustrate recent progress made in that direction.