Simulation-based Algorithms for Markov Decision Processes, Hyeong Soo Chang; Michael C. Fu; Jiaqiao Hu; Steve
Автор: Asmussen Название: Stochastic Simulation: Algorithms and Analysis ISBN: 038730679X ISBN-13(EAN): 9780387306797 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University.
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: 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: 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: 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.
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: Ogrodzki Название: Circuit Simulation Methods and Algorithms ISBN: 084937894X ISBN-13(EAN): 9780849378942 Издательство: Taylor&Francis Рейтинг: Цена: 33686.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Circuit Simulation Methods and Algorithms provides a step-by-step theoretical consideration of methods, techniques, and algorithms in an easy-to-understand format
Автор: Luca Marchetti; Corrado Priami; Vo Hong Thanh Название: Simulation Algorithms for Computational Systems Biology ISBN: 331963111X ISBN-13(EAN): 9783319631110 Издательство: Springer Рейтинг: Цена: 7965.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics.
Описание: Written by Ron Alterovitz and Ken Goldberg, this monograph combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures.
Автор: S?ren Asmussen; Peter W. Glynn Название: Stochastic Simulation: Algorithms and Analysis ISBN: 144192146X ISBN-13(EAN): 9781441921468 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a broad treatment of sampling-based computational methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. General methods and model-specific algorithms are discussed.
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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