Algorithms for Decision Making (MIT Press)

This book provides a general introduction to algorithms for decision making under uncertainty, covering the formulations of underlying mathematical problems and the algorithms for solving them. Mykel Kochenderfer and Tim Wheeler first address the problem of reasoning about uncertainty and goals in simple decisions at a given time, then turn to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain .

The book then addresses model uncertainty, when we do not start from a known model and must learn to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. The algorithms are implemented in Julia.

Author: Mykel Kochenderfer and Tim Wheeler
Publisher: MIT Press
Date: August 2022
Pages: 700
ISBN: 978-0262047012
Printing: 0262047012
Kindle: B09RF2WCQS
Audience: General
Level: Intermediate/Advanced
Category: Theory & Techniques

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Sharon D. Cole