Applications of Reinforcement Learning
RL has exciting and useful applications in many different contexts. Recently, the usage of deep neural networks has augmented the number of possible applications considerably.
When used in a deep learning context, RL can also be referred to as deep RL.
The applications vary from games and video games to real-world applications, such as robotics and autonomous driving. In each of these applications, RL is a game-changer, allowing you to solve tasks that are considered to be almost impossible (or, at least, very difficult) without these techniques.
In this section, we will present some RL applications, describe the challenges of each application, and begin to understand why RL is preferred among other methods, along with its advantages and its drawbacks.
Games
Nowadays, RL is widely used in video games and board games.
Games are used to benchmark RL algorithms because, usually, they are very complex to solve yet easy to implement...