Understanding approximate dynamic programming (ADP) in large industrial settings helps develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, this second edition of Approximate Dynamic Programming Solving the Curses of Dimensionality uniquely integrates four distinct disciplines-Markov design processes, mathematical programming, simulation, and statistics-to show students, practitioners, and researchers how to successfully model and solve a wide range of real-life problems using ADP.