<電子ブック>
Markov Decision Processes with Their Applications / by Qiying Hu, Wuyi Yue
(Advances in Mechanics and Mathematics. ISSN:18769896 ; 14)
版 | 1st ed. 2008. |
---|---|
出版者 | (New York, NY : Springer US : Imprint: Springer) |
出版年 | 2008 |
本文言語 | 英語 |
大きさ | XV, 297 p : online resource |
著者標目 | *Hu, Qiying author Yue, Wuyi author SpringerLink (Online service) |
件 名 | LCSH:Operations research LCSH:Management science LCSH:Probabilities LCSH:Mathematical optimization LCSH:Calculus of variations LCSH:Industrial engineering LCSH:Production engineering FREE:Operations Research, Management Science FREE:Probability Theory FREE:Calculus of Variations and Optimization FREE:Industrial and Production Engineering |
一般注記 | Discretetimemarkovdecisionprocesses: Total Reward -- Discretetimemarkovdecisionprocesses: Average Criterion -- Continuous Time Markov Decision Processes -- Semi-Markov Decision Processes -- Markovdecisionprocessesinsemi-Markov Environments -- Optimal control of discrete event systems: I -- Optimal control of discrete event systems: II -- Optimal replacement under stochastic Environments -- Optimalal location in sequential online Auctions Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters. Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents four main topics that are used to study optimal control problems: *a new methodology for MDPs with discounted total reward criterion; *transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; *MDPs in stochastic environments, which greatly extends the area where MDPs can be applied; *applications of MDPs in optimal control of discrete event systems, optimal replacement, and optimal allocation in sequential online auctions. This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce HTTP:URL=https://doi.org/10.1007/978-0-387-36951-8 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
Springer eBooks | 9780387369518 |
|
電子リソース |
|
EB00237568 |
書誌詳細を非表示
データ種別 | 電子ブック |
---|---|
分 類 | LCC:T57.6-57.97 LCC:T55.4-60.8 DC23:3 |
書誌ID | 4000119902 |
ISBN | 9780387369518 |
類似資料
この資料の利用統計
このページへのアクセス回数:2回
※2017年9月4日以降