Algorithms for Decision Making

Algorithms for Decision Making, by Mykel J. Kochenderfer, is a textbook that gives a broad introduction to algorithms for decision making under uncertainty, together with the underlying mathematical problem formulations. The MIT Press published this 700-page hardcover in 2022.

The book first addresses simple decisions at a single point in time, then turns to sequential decision problems in stochastic environments. It goes on to address model uncertainty, state uncertainty, and decision contexts involving multiple agents. Algorithms are implemented in the Julia programming language, and figures, examples, and exercises convey the intuition behind each approach.

The focus is primarily on planning and reinforcement learning, with some techniques drawn from supervised learning and optimization.