Dynamic Optimization: Deterministic and Stochastic Models (Universitext)
Provides a self-contained and easy-to-read introduction todynamic programmingProvides a comprehensive treatment of discrete-time multistageoptimizationPresents the theory of Markov decision processes withoutadvanced measure theoryIncludes various examples and exercises (withoutsolutions)——————————This book explores discrete-time dynamic optimization andprovides a detailed introduction to both deterministic andstochastic models. Covering problems with finite and infinitehorizon, as well as Markov renewal programs, Bayesian controlmodels and partially observable processes, the book focuses on theprecise modelling of applications in a variety of areas, includingoperations research, computer science, mathematics, statistics,engineering, economics and finance.Dynamic Optimization is a carefully presented textbookwhich starts with discrete-time deterministic dynamic optimizationproblems, providing readers with the tools for sequentialdecision-making, before proceeding to the more complicatedstochastic models. The authors present complete and simple proofsand illustrate the main results with numerous examples andexercises (without solutions). With relevant material covered infour appendices, this book is completely self-contained.