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.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.
https://www.amazon.com/Data-Driven-Science-Engineering-Learn...
Have a wonderful day =)