Dynamic Programming: Models and Applications (Dover Books on Computer Science)

It's written during the 80s. So it's good as an introduction book.

I'm in a Dynamic Programming class right now and this book has a few things going for it and one big detractor.First, it's cheap! Every semester I have to buy books I cringe at the end price tag but this time it wasn't that bad.Second, it's a relatively easy read. By this I mean there are short chapters, big font and it doesn't take a long time to get through a lessons reading assignment.Third, it's got some good examples that help me in understanding things but I often have to reread sections to get a full understanding of something.Now for the downside. Up until now I never thought I would want a book to contain more, but that's exactly what I'm looking for from this book. I often feel like I don't quite get a topic before we move on to the next section but there just is so little in the book that when I'm left wanting, there is little to help me get a topic.Finally, regarding the edition of this book. Just so everyone knows, this paperback is just a reprint of the hardbound from 1992. It is not a new edition, and there are no changes in content. They added an intro for the "Dover Edition" and bound it soft cover, but everything else is the same. The hardbound would be a great choice for people trying to save a buck if this wasn't already so cheap.

Standard book on dynamic programming

Outstanding text useful in learning the basics of dynamic programming.

excelent bookk for instructors master and PhD in Operarions Reserch

I ordered this as it was the required text book for a graduate class in Dynamic Programming. I would suggest that be the only reason you would ever buy this book. The only positive is that it is inexpensive! Denardo is a big guy in DP and clearly knows his stuff but just communicates it very badly, the exercises are ambiguous and the whole thing is badly written! Of course all this is my opinion - you may love it but be warned!

Dynamic programming is a rich modeling framework for sequential decision problems. Despite its key ideas being mathematically simple, they are far from trivial. This short book by Denardo is one of the primary references I have come across. Although the field has changed a lot since 1982 (the original publishing year) and turned to reinforcement learning, Denardo provides us with many insights and rigorous math, often lacking in current RL books or research. He makes it clear the definition of states, its difference from the notion of stage, the idea of embedding, and provides many insights on how to model a problem. Indispensable reading for people who want to delve into DP and RL theory.