Customer Rating:
Summary: From the author of Approximate Dynamic Programming
Comment: If you believe in the axiom "less is more," this is an outstanding book. This is the book that attracted me to the field of dynamic programming. The presentation is exceptionally clear, and gives an introduction to the simple, elegant problems that makes the field so addictive. It takes only a few afternoons to go through the entire book. In fact, it was memories of this book that guided the introduction to my own book on approximate dynamic programming (see chapter 2).

Once you have been drawn to the field with this book, you will want to trade up to Puterman's much more thorough presentation in Markov Decision Processes: Discrete Stochastic Dynamic Programming (Wiley Series in Probability and Statistics). But be forewarned - this elegant theory, which uses a "flat representation" of states (where states are numbered 1, 2, ..., S), suffers from the well-known curse of dimensionality, limiting its practical application. If your interests are drawn to real problems, you might consider my recent book Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics), which puts far more emphasis on modeling and practical algorithms drawn from the field of approximate dynamic programming. Other important references in this field are Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3), and Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning).

Warren B. Powell
Professor
Princeton University

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Customer Rating:
Summary: Good Examples BUT...a little too theoretical
Comment: I've used this book for a graduate course in Dynamic Programming. Having used many of Mr. Ross's books (undergraduate and graduate), I found this one lacks the detail and lucidity (particularly the end of chapter problems...I believe in "learning by doing"... i.e. solve lots of problems!) that I have come to know of his books (e.g. A First Course in Probability and Introduction to Probability Models). The bright spot of the book is its examples, which are interesting and fairly detailed.

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