At this point, we are briefly going to introduce the three essential concepts in reinforcement learning: states, actions, and rewards. In this section, we will give you minimal information so that you can understand the practical exercise in this chapter. In this case, we are applying the strategy of focus on the practice to really understand the theory.
This method of focus on the practice to really understand the theory is especially required for complex topics that are better understood if you follow an empirical approach with easy-to-run examples. This preliminary practical success should provide you with enough motivation to get deeper into the topic, a task that in any case will be hard both in the algorithms and in the mathematics behind them.
So, let's proceed to define these core concepts involved in the learning task of the robot...
