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Dynamic Programming and Its Applications provides information pertinent to the theory and application of dynamic programming. This book presents the development and future directions for dynamic programming.
Organized into four parts encompassing 23 chapters, this book begins with an overview of recurrence conditions for countable state Markov decision problems, which ensure that the optimal average reward exists and satisfies the functional equation of dynamic programming. This text then provides an extensive analysis of the theory of successive approximation for Markov decision problems. Other chapters consider the computational methods for deterministic, finite horizon problems, and present a unified and insightful presentation of several foundational questions. This book discusses as well the relationship between policy iteration and Newton's method. The final chapter deals with the main factors severely limiting the application of dynamic programming in practice.
This book is a valuable resource for growth theorists, economists, biologists, mathematicians, and applied management scientists.
Recurrence Conditions in Denumerable State Markov Decision Processes
Discounted and Undiscounted Value-Iteration in Markov Decision Problems: A Survey
Computational Advances in Dynamic Programming
The Analytic Theory of Policy Iteration
Dynamic Programming in Borei Spaces
Elimination of Nonoptimal Actions in Markov Decision Processes
On Renewal Decisions
Steady-State Policies, Dynamic Programming, and Optimal Economic Growth
Comments on the Origin and Application of Markov Decision Processes
The Application of Markov Decision Processes to Forest Management
An Application of Dynamic Programming in Statistics
Some Dynamic Programming Applications in Fisheries Management
Buckets, Shortest Paths, and Integer Programming
Affine Dynamic Programming
Optimal Control of a Diffusion Process with Reflecting Boundaries and both Continous and Lump Costs
On Approximate Solutions of Finite-Stage Dynamic Programs
An Inverse Theorem between Main and Inverse Dynamic Programming: Infinite-Stage Case
On the Transient Case for Markov Decision Chains with General State Spaces
An Operator-Theoretical Treatment of Negative Dynamic Programming
Existence of Average Optimal Strategies in Markovian Decision Problems with Strictly Unbounded Costs
International Conference on Dynamic Programming: Panel Discussion
Comments Of Karl Hinderer
Comments Of Eric V. Denardo
Comments Of Arthur F. Veinott, Jr.
- No. of pages:
- © Academic Press 1978
- 1st January 1978
- Academic Press
- eBook ISBN: