RL is a very important area but is sometimes overlooked by practitioners for solving complex, real-world problems. It is unfortunate that even most ML textbooks focus only on supervised and unsupervised learning while totally ignorning RL.
RL as an area has picked up momentum in recent years; however, its origins date back to 1980. It was invented by Rich Sutton and Andrew Barto, Rich's PhD thesis advisor. It was thought of as archaic, even back in the 1980s. Rich, however, believed in RL and its promise, maintaining that it would eventually be recognized.
A quick Google search with the term RL shows that RL methods are often used in games, such as checkers and chess. Gaming problems are problems that require taking actions over time to find a long-term optimal solution to a dynamic problem. They are dynamic in the sense that the conditions are constantly changing, sometimes in response to other agents, which can be adversarial.
Although the success of RL is proven in the...