They have kindly allowed me to provide free of charge a pre-publication draft.
The organization is unique:
- Part I: Fundamentals Without Noise
- Part II: Reinforcement Learning and Stochastic Control
The first half of the book is accessible to a reader without any background in probabilistic methods. Undergraduate probability is desirable, but far more important is calculus and linear algebra (the same background required for a first course covering state space models and control).
A new course based on Part I of the book was introduced at UF in the spring of 2021. The course is unique in part because no probability theory is required.