ADVANCES IN MECHANICS AND MATHEMATICS
Qiying Yue Wuyi Hu
Oprawa:
TWARDA
Wydawca:
Springer US
ISBN:
9780387369501
Opis produktu
Put together by two top researchers in the Far East this text examines Markov Decision Processes also called stochastic dynamic programming and their applications in the optimal control of discrete event systems optimal replacement and optimal allocations in sequential online auctions. This dynamic new book offers fresh applications of MDPs in areas such as the control of discrete event systems and the optimal allocations in sequential online auc/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. 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 comMarkov decision processes (MDPs) also called stochastic dynamic programming were first studied in the 1960s. MDPs can be used to model and solve dynamic decisionmaking problems that are multiperiod and occur in stochastic circumstances. There are three basic branches in MDPs: discretetime MDPs continuoustime MDPs and semiMarkov 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 continuoustime MDPs and semiMarkov decision processes into a discretetime 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 comDiscretetimemarkovdecisionprocesses: Total Reward. Discretetimemarkovdecisionprocesses: Average Criterion. Continuous Time Markov Decision Processes. SemiMarkov Decision Processes. MarkovdecisionprocessesinsemiMarkov Environments. Optimal control of discrete event systems: I. Optimal control of discrete event systems: II. Optimal replacement under stochastic Environments. Optimalal location in sequentialFrom the reviews://Markov decision processes (MDPs) are one of the most comprehensively investigated braWymiary: 1370 gr 155 mm 235 mm
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632 237
Ostatnia aktualizacja:
28-03-2024