The challenging task of autonomously learning skills without the help of a teacher, solely based on feedback from the environment to actions, is called reinforcement learning. Still being an active area of research, some impressive results can be shown on robots. Reinforcement learning enables robots to learn motor skills as well as simple cognitive behavior. We use a simple robot with only two degrees of freedom to demonstrate the strengths of the value iteration and Q-learning algorithms, as well as their limitations.