LIKE NEW: This book is in excellent condition and doesn't appear to have been used. It is printed on acid-free paper.
Product Details
From the back cover: "This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. Stochastic control problems are treated using the dynamic programming approach. The authors approach stochastic control problems by the method of dynamic programming. The fundamental equation of dynamic programming is a nonlinear evolution equation for the value function. For controlled Markov diffusion processes, this becomes a nonlinear partial differential equation of second order, called a Hamilton-Jacobi-Bellman (HJB) equation. Typically, the value function is not smooth enough to satisfy the HJB equation in a classical sense. Viscosity solutions provide framework in which to study HJB equations, and to prove continuous dependence of solutions on problem data. The theory is illustrated by applications from engineering, management science, and financial economics."
BRIEF CONTENTS
Preface to Second Edition
Preface
Notation
I - Deterministic Optimal Control
II - Viscosity Solutions
III - Optimal Control of Markov Processes: Classical Solutions
IV - Controlled Markov Diffusions in IRn
V - Viscosity Solutions: Second-Order Case
VI - Logarithmic Transformations and Risk Sensitivity
VII - Singular Perturbations
VIII - Singular Stochastic Control
IX - Finite Difference Numerical Approximations
X - Applications to Finance
XI - Differential Games
A - Duality Relationships
B - Dynkin's Formula for Random Evolutions with Markov Chain Parameters
C - Extension of Lipschitz Continuous Functions; Smoothing
D - Stochastic Differential Equations: Random Coefficients
