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: 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: 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: A.V. Gheorghe Название: Decision Processes in Dynamic Probabilistic Systems ISBN: 0792305442 ISBN-13(EAN): 9780792305446 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Et moi -...- si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais point aile: human race. It has put common sense back where it belongs. on the topmost shelf next Jules Verne (0 the dusty canister labelled 'discarded non- sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non- linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com- puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
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.
Автор: A.V. Gheorghe Название: Decision Processes in Dynamic Probabilistic Systems ISBN: 9401067082 ISBN-13(EAN): 9789401067089 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Baoding Liu; Augustine O. Esogbue Название: Decision Criteria and Optimal Inventory Processes ISBN: 146137345X ISBN-13(EAN): 9781461373452 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision Criteria and Optimal Inventory Processes provides a theoretical and practical introduction to decision criteria and inventory processes.
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.
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