Algorithms for Decision Making

Mykel Kochenderfer, Tim Wheeler, and Kyle Wray, Algorithms for Decision Making, MIT Press, 2022. (pdf available online)

A broad introduction to algorithms for optimal decision making under uncertainty. We cover a wide variety of topics related to decision making, introducing the underlying mathematical problem formulations and the algorithms for solving them. Figures, examples, and exercises are provided to convey the intuition behind the various approaches. This text is intended for advanced undergraduates and graduate students as well as professionals. The book requires some mathematical maturity and assumes prior exposure to multivariable calculus, linear algebra, and probability concepts. Some review material is provided in the appendix. Disciplines where the book would be especially useful include mathematics, statistics, computer science, aerospace, electrical engineering, and operations research. Fundamental to this textbook are the algorithms, which are all implemented in the Julia programming language.

Prof. Kochenderfer also teaches 2 related courses at Stanford.