Algorithms for Decision Making

by Mykel J. Kochenderfer, Tim A Wheeler, Kyle H Wray

This book provides a broad introduction to algorithms for 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.

Genres: Computer Science, Programming, Mathematics, Artificial Intelligence, Textbooks, Technology, Algorithms

688 pages, Unknown Binding

Published January 1, 2021

Reviews

[Alireza Hejazi · Rating 4 out of 5]

This book gives an informative overview of algorithms for making decisions under uncertain conditions. Many essential tasks, such as airplane crash avoidance, wildfire control, and disaster response, require decision-making under uncertainty. It is critical to account for numerous sources of uncertainty while carefully balancing several objectives when building automated decision-making systems or decision-support systems. This book addresses these issues from a computational standpoint, intending to provide the theory behind decision-making models and computational methods. It presents the topic of decision-making under uncertainty, offers examples, and sketches the computational method space. Readers who are interested in how many disciplines have contributed to our understanding of intelligent decision making, as well as areas of potential social effect, may find the book fascinating. Because of its educational design and extensive material, it may successfully serve as a textbook for college students.