The "Trough of disillusionment" always hits every paradigm shift in markets.

https://en.wikipedia.org/wiki/Gartner_hype_cycle

In general, people tend to learn most subjects through their own actions and continuous practice... and not through abstract imagination of some non sequitur that lecturers may not even fully comprehend. Only 1:17 people have the self discipline to do self-directed study... online that stat is likely more dismal... =)

Yet, we found Steve Brunton's book and many labs tended to engage people better than handouts:

https://www.youtube.com/@Eigensteve/videos

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

Thanks Steve =3

I hadn't known about this, so thank you! Steven Brunton also has a book that covers dynamical systems (among other things) which is linear algebra adjacent, and the expositions are great [1].

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

Highly recommended book, they also have a paper copy if you want to support their work. Very pleasing to see other people noticed they updated the text.

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

Have a wonderful day =)

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.