Skip to Main Content
Dynamic Programming is a fundamental tool widely used to model and solve various sequential decision making under uncertainty. This course is developed to study the popular concepts and techniques of dynamic programming. The contents include Principles of Optimality; Deterministic Dynamic Programming Problems; Stochastic Dynamic Programming Problems with Perfect and Imperfect Information; Infinite Horizon Problem and Dynamic Programming Algorithm. Some applications of Approximate Dynamic Programming, especially for problems from operations research and computer science will be discussed.
The first of the two volumes of the leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization.
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
