It has been my experience that you can see into the soul of a book through a good index. The index for my upcoming: Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions
I have to emphasize that I am taking a very broad view of "reinforcement learning," since I think this is the direction the field has been taking over the past 20 years. In
chapter 2 I give a brief overview of 15 different fields (in section 2.1), I pull all of these together into my universal framework in section 2.2 For people who have never encountered these fields, skimming section 2.1 can be a nice tour. Note that *all* of these fields can be approached using the tools of reinforcement learning.