Описание: This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.
Автор: Jerzy Filar; Koos Vrieze Название: Competitive Markov Decision Processes ISBN: 1461284813 ISBN-13(EAN): 9781461284819 Издательство: Springer Рейтинг: Цена: 20677.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Since Markov decision processes can be viewed as a special noncompeti tive case of stochastic games, we introduce the new terminology Competi tive Markov Decision Processes that emphasizes the importance of the link between these two topics and of the properties of the underlying Markov processes.
Автор: Sheskin, Theodore J. Название: Markov Chains and Decision Processes for Engineers and Managers ISBN: 0367383438 ISBN-13(EAN): 9780367383435 Издательство: Taylor&Francis Рейтинг: Цена: 10104.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly prescriptive, with little justification for the steps of the algorithms used to solve Markov models. Providing a unified treatment of Markov chains and Markov decision processes in a single volume, Markov Chains and Decision Processes for Engineers and Managers supplies a highly detailed description of the construction and solution of Markov models that facilitates their application to diverse processes.
Organized around Markov chain structure, the book begins with descriptions of Markov chain states, transitions, structure, and models, and then discusses steady state distributions and passage to a target state in a regular Markov chain. The author treats canonical forms and passage to target states or to classes of target states for reducible Markov chains. He adds an economic dimension by associating rewards with states, thereby linking a Markov chain to a Markov decision process, and then adds decisions to create a Markov decision process, enabling an analyst to choose among alternative Markov chains with rewards so as to maximize expected rewards. An introduction to state reduction and hidden Markov chains rounds out the coverage.
In a presentation that balances algorithms and applications, the author provides explanations of the logical relationships that underpin the formulas or algorithms through informal derivations, and devotes considerable attention to the construction of Markov models. He constructs simplified Markov models for a wide assortment of processes such as the weather, gambling, diffusion of gases, a waiting line, inventory, component replacement, machine maintenance, selling a stock, a charge account, a career path, patient flow
Автор: Hyeong Soo Chang; Jiaqiao Hu; Michael C. Fu; Steve Название: Simulation-Based Algorithms for Markov Decision Processes ISBN: 144715990X ISBN-13(EAN): 9781447159902 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The updated 2nd edition of this book covers MDPs in constrained settings and with uncertain transition properties; approximation stochastic annealing, a population-based on-line simulation-based algorithm; game-theoretic method for solving MDPs and more.
Автор: Hyeong Soo Chang; Michael C. Fu; Jiaqiao Hu; Steve Название: Simulation-based Algorithms for Markov Decision Processes ISBN: 1849966435 ISBN-13(EAN): 9781849966436 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.
Описание: This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields.
Автор: Boucherie Richard J., Van Dijk Nico M. Название: Markov Decision Processes in Practice ISBN: 3319838172 ISBN-13(EAN): 9783319838175 Издательство: Springer Рейтинг: Цена: 39130.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach.
Автор: Eugene A. Feinberg; Adam Shwartz Название: Handbook of Markov Decision Processes ISBN: 1461352487 ISBN-13(EAN): 9781461352488 Издательство: Springer Рейтинг: Цена: 48913.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems.
Автор: Chang Hyeong Soo Название: Simulation-based Algorithms for Markov Decision Processes ISBN: 144715021X ISBN-13(EAN): 9781447150213 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The updated 2nd edition of this book covers MDPs in constrained settings and with uncertain transition properties; approximation stochastic annealing, a population-based on-line simulation-based algorithm; game-theoretic method for solving MDPs and more.
Автор: Qiying Hu; Wuyi Yue Название: Markov Decision Processes with Their Applications ISBN: 1441942386 ISBN-13(EAN): 9781441942388 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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.
Автор: Richard Boucherie; Nico M van Dijk Название: Markov Decision Processes in Practice ISBN: 3319477641 ISBN-13(EAN): 9783319477640 Издательство: Springer Рейтинг: Цена: 30745.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach.
Автор: Zhenting Hou; Jerzy A. Filar; Anyue Chen Название: Markov Processes and Controlled Markov Chains ISBN: 1402008031 ISBN-13(EAN): 9781402008030 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Researchers in Markov processes and controlled Markov chains have been aware of the synergies between these two subject areas. This volume highlights these synergies and emphasizes the contributions of the Chinese school of probability. The chapters reflect both the maturity and the vitality of Markov processes and controlled Markov chains.
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