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Handbook of Markov Decision Processes

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Feinberg, Egene A.; Shwartz, Adam; Feinberg, Eugene A. 作者
Springer
译者
2001-08-01 出版日期
573 页数
USD 245.00 价格
Hardcover
丛书系列
9780792374596 图书编码

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Handbook of Markov Decision Processes 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Handbook of Markov Decision Processes 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Handbook of Markov Decision Processes 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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The theory of Markov Decision Processes - also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming - studies sequential optimization of discrete time stochastic systems. Fundamentally, this is a methodology that examines and analyzes a discrete-time stochastic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. Its objective is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types of impacts: (i) they cost or save time, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view of future events. Markov Decision Processes (MDPs) model this paradigm and provide results on the structure and existence of good policies and on methods for their calculations. MDPs are attractive to many researchers because they are important both from the practical and the intellectual points of view. MDPs provide tools for the solution of important real-life problems. In particular, many business and engineering applications use MDP models. Analysis of various problems arising in MDPs leads to a large variety of interesting mathematical and computational problems. Accordingly, the Handbook of Markov Decision Processes is split into three parts: Part I deals with models with finite state and action spaces and Part II deals with infinite state problems, and Part III examines specific applications. Individual chapters are written by leading experts on the subject.

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