Kalman filters and variations are covered in Ch. 19. It can be viewed as a special case of belief updating in a partially observable Markov decision process.
This is a very important dimension. See Sec. 1.5 of the book. There is also a side reference to a book that discusses this and other societal implications.
You are right that sometimes people use much more sophisticated algorithms than are really required to solve a problem. My experience is that the simplest approach is often the best one in the long term. There are actually deep connections between problems in control theory and the topics in this book (e.g., LQR control), though these different communities often use different notation. The focus of the book is more on higher-level decision making, but the execution of the decisions---such as motor commands to an actuator---are often best done through PID or some other method that can be found in a control theory textbook.