This repository serves as a starter kit for learners to pick up the essential theories of reinforcement learning. The approach taken in this repository is to focus on the fundamental theories behind reinforcement learning and stochastic optimal control before jumping into application. As a start, most of the materials are inspired by Prof. Dimitri P. Bertsekas. References to the books and materials will be cited, but the e-books will not be uploaded on this repository. E-books that are freely available online would be obtainable from Prof Bertsekas' webpage, which the link is provided.
A personally curated summary notes will be provided, and will cite the reference materials accordingly. Practice exercises (coding and non-coding) may be found in this repository, with my suggested answers.
All the best to your learning and enjoy!