I'd say RL is an advanced robotics topic. There are some books out there that cover introductory or general RL aspects... after that you'll have to dive into papers and specific code bases.

Might not be a bad idea to start with a Python-based, practical RL book and move from practical demonstrations towards theory.

Although not an RL book, I really like Data-Driven Science and Engineering by Brunton and Kutz:

- https://www.databookuw.com/

- https://www.amazon.com/Data-Driven-Science-Engineering-Learn...

Steve Brunton also has an awesome youtube channel on dynamic systems, control, and machine learning.

Robotic books with some RL concepts (don't have either of these tbh):

- https://introduction-to-autonomous-robots.github.io/

- https://mitpress.mit.edu/9780262046169/learning-for-adaptive...

General texts/resources on adaptive control, optimal control, and RL:

- https://arxiv.org/abs/1912.03513

- http://www.cs.cmu.edu/~cga/dynopt/

- http://www.mit.edu/~dimitrib/RLbook.html

Practical Methods for Optimal Control Using Nonlinear Programming, Third Edition by John Betts:

- https://my.siam.org/Store/Product/viewproduct/?ProductId=316...

Adaptive Control Tutorial by Ioannou and Fidan

- https://mitpress.mit.edu/9780262039246/reinforcement-learnin...

Control Systems and Reinforcement Learning by Sean Meyn looks to be on topic but I haven't read through it.

Thanks for the list.