We do have imitation Learning. I think the article is missing some important parts in RL. One way to train a network is to use experience from others or even past experience of the agent, but why is it interesting doing it from scratch? Because doing it from scratch will allow us to face a lot more problems where we don't have any information or skills and because we avoid the bias in the data and we can discover new things (as it happened with AlphaGo zero with its 'tactics' in go). Now we have a method that can be applied to all the problems that are similar to a board game without any other information, just the rules of the domain.