Dynamic Optimization - Deterministic and Stochastic Models (Paperback, 1st ed. 2016)

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Universitext
Release date:	2017
First published:	2016
Authors:	Karl Hinderer • Ulrich Rieder • Michael Stieglitz
Dimensions:	235 x 155 x 32mm (L x W x T)
Format:	Paperback
Pages:	530
Edition:	1st ed. 2016
ISBN-13:	978-3-319-48813-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Science & Mathematics > Mathematics > Optimization > General Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics Promotions
LSN:	3-319-48813-9
Barcode:	9783319488134

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