Real-world examples of reinforcement learning

Let's see where RL occurs in the real world. This will help us understand how it works and what possible applications can be built using this concept:

Game playing – Let's consider a board game like Go or Chess. In order to determine the best move, the players need to think about various factors. The number of possibilities is so large that it is not possible to perform a brute-force search. If we were to build a machine to play such a game using traditional techniques, we would need to specify many rules to cover all these possibilities. RL completely bypasses this problem. We do not need to manually specify any logic rules. The learning agent simply learns by example and playing games against itself.

For a more thorough discussion on this topic refer to the Gaming section in Chapter 2, Fundamental Use Cases for Artificial Intelligence.

Robotics – Let's consider a robot whose...