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Markov Decision Processes: Discrete Stochastic Dynamic Programming, Martin L. Puterman



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Автор: Martin L. Puterman   (Мартин Л. Путерман)
Название:  Markov Decision Processes: Discrete Stochastic Dynamic Programming   (Мартин Л. Путерман: Марковские процессы принятия решений. Дискретное стохастическое динамическое про)
Издательство: Wiley
Классификация:
МАТЕМАТИКА
Вероятность и статистика

ISBN: 0471727822
ISBN-13(EAN): 9780471727828
ISBN: 0-471-72782-2
ISBN-13(EAN): 978-0-471-72782-8
Обложка/Формат: Paperback
Страницы: 650
Вес: 0.992 кг.
Дата издания: February 25, 2005
Серия: Wiley series in probability and statistics
Язык: English
Издание: 2 rev ed
Иллюстрации: Illustrations
Размер: 234 x 155 x 32
Читательская аудитория: Professional & vocational
Подзаголовок: Discrete stochastic dynamic programming
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: The Wiley--Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. This text is unique in bringing together so many results hitherto found only in part in other texts and papers...The text is fairly self--contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential. - Zentralblatt fur Mathematik ...it is of great value to advanced--level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic...Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up--to--date, unified, and rigorous tre - Journal of the American Statistical Association
Дополнительное описание: Кол-во стр.: 650
Формат: 235 x 156
Дата издания: 2005
Вес: 841





      Старое издание
Markov decision processes :

Автор: Puterman, Martin L.
Название: Markov decision processes :
ISBN: 0471619779 ISBN-13(EAN): 9780471619772
Издательство: Неизвестно
Цена: р.
Наличие на складе: Невозможна поставка.


Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 6901 р.
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Описание: This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instils a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to modelling real-world systems. It includes a careful review of elementary probability and detailed coverage of Poisson, Gaussian and Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks, large deviations, martingales and investments are developed. Written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching and enriched by over 300 exercises, this is an exceptional resource for anyone looking to develop their understanding of stochastic processes.

Handbook of Markov Decision Processes / Methods and Applications

Автор: Feinberg Eugene A., Shwartz Adam
Название: Handbook of Markov Decision Processes / Methods and Applications
ISBN: 0792374592 ISBN-13(EAN): 9780792374596
Издательство: Springer
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Цена: 31246 р.
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Описание: The theory of Markov Decision Processes - also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming - studies sequential optimization of discrete time stochastic systems. Fundamentally, this is a methodology that examines and analyzes a discrete-time stochastic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. Its objective is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types of impacts: (i) they cost or save time, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view of future events. Markov Decision Processes (MDPs) model this paradigm and provide results on the structure and existence of good policies and on methods for their calculations. MDPs are attractive to many researchers because they are important both from the practical and the intellectual points of view. MDPs provide tools for the solution of important real-life problems. In particular, many business and engineering applications use MDP models. Analysis of various problems arising in MDPs leads to a large variety of interesting mathematical and computational problems. Accordingly, the Handbook of Markov Decision Processes is split into three parts: Part I deals with models with finite state and action spaces and Part II deals with infinite state problems, and Part III examines specific applications. Individual chapters are written by leading experts on the subject.

Markov Decision Processes with Their Applications

Автор: Hu Qiying, Yue Wuyi
Название: Markov Decision Processes with Their Applications
ISBN: 0387369503 ISBN-13(EAN): 9780387369501
Издательство: Springer
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Цена: 17241 р.
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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 multiperiod and 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. MDPs have been applied in many areas, such as communications, signal processing, artificial intelligence, stochastic scheduling and manufacturing systems, discrete event systems, management and economies.This book 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 three main topics: вЂў a new methodology for MDPs with discounted total reward criterion; вЂў transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; вЂў application of MDPs in stochastic environments, which greatly extends the area where MDPs can be applied.Each topic is used to study optimal control problems or other types of problems.

Discrete-Time Markov Control Processes

Автор: Hernandez-Lerma
Название: Discrete-Time Markov Control Processes
ISBN: 0387945792 ISBN-13(EAN): 9780387945798
Издательство: Springer
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Цена: 13584 р.
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Описание: This text provides a unified treatment of some recent theoretical developments on Markov control processes. Interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbound costs and non-compact control constraint sets.

Further Topics on Discrete-Time Markov Control Processes

Автор: Hernandez-Lerma
Название: Further Topics on Discrete-Time Markov Control Processes
ISBN: 0387986944 ISBN-13(EAN): 9780387986944
Издательство: Springer
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Цена: 14629 р.
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Описание: Devotes to a systematic exposition of some developments in the theory of discrete-time Markov control processes.

Continuous-Time Markov Decision Processes

Автор: Guo
Название: Continuous-Time Markov Decision Processes
ISBN: 3642025463 ISBN-13(EAN): 9783642025464
Издательство: Springer
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Цена: 10449 р.
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Описание: Theory and Applications. .

Markov Decision Processes in Practice

Автор: Richard Boucherie; Nico M van Dijk
Название: Markov Decision Processes in Practice
ISBN: 3319477641 ISBN-13(EAN): 9783319477640
Издательство: Springer
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Цена: 22989 р.
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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.

Limit Theorems for Markov Chains and Stochastic Properties of Dynamical Systems by Quasi-Compactness

Автор: Hennion Hubert, Herve Loic
Название: Limit Theorems for Markov Chains and Stochastic Properties of Dynamical Systems by Quasi-Compactness
ISBN: 3540424156 ISBN-13(EAN): 9783540424154
Издательство: Springer
Цена: 3652 р.
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Описание: This book shows how techniques from the perturbation theory of operators, applied to a quasi-compact positive kernel, may be used to obtain limit theorems for Markov chains or to describe stochastic properties of dynamical systems.A general framework for this method is given and then applied to treat several specific cases. An essential element of this work is the description of the peripheral spectra of a quasi-compact Markov kernel and of its Fourier-Laplace perturbations. This is first done in the ergodic but non-mixing case. This work is extended by the second author to the non-ergodic case.The only prerequisites for this book are a knowledge of the basic techniques of probability theory and of notions of elementary functional analysis.

Markov chains and stochastic stability

Автор: Meyn, Sean Tweedie, Richard L.
Название: Markov chains and stochastic stability
ISBN: 0521731828 ISBN-13(EAN): 9780521731829
Издательство: Cambridge Academ
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Цена: 7476 р.
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Описание: Meyn & Tweedie is back! The bible on Markov chains in general state spaces has been brought up to date to reflect developments in the field since 1996 - many of them sparked by publication of the first edition. The pursuit of more efficient simulation algorithms for complex Markovian models, or algorithms for computation of optimal policies for controlled Markov models, has opened new directions for research on Markov chains. As a result, new applications have emerged across a wide range of topics including optimisation, statistics, and economics. New commentary and an epilogue by Sean Meyn summarise recent developments and references have been fully updated. This second edition reflects the same discipline and style that marked out the original and helped it to become a classic: proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background.

Markov Processes, Brownian Motion, and Time Symmetry

Автор: Chung
Название: Markov Processes, Brownian Motion, and Time Symmetry
ISBN: 0387220267 ISBN-13(EAN): 9780387220260
Издательство: Springer
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Цена: 12326 р.
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Описание: From the reviews of the First Edition:"This excellent book is based on several sets of lecture notes written over a decade and has its origin in a one-semester course given by the author at the ETH, ZГјrich, in the spring of 1970. The author's aim was to present some of the best features of Markov processes and, in particular, of Brownian motion with a minimum of prerequisites and technicalities. The reader who becomes acquainted with the volume cannot but agree with the reviewer that the author was very successful in accomplishing this goal…The volume is very useful for people who wish to learn Markov processes but it seems to the reviewer that it is also of great interest to specialists in this area who could derive much stimulus from it. One can be convinced that it will receive wide circulation." (Mathematical Reviews)This new edition contains 9 new chapters which include new exercises, references, and multiple corrections throughout the original text.

Semigroups, Boundary Value Problems and Markov Processes

Автор: Taira Kazuaki
Название: Semigroups, Boundary Value Problems and Markov Processes
ISBN: 3540406514 ISBN-13(EAN): 9783540406518
Издательство: Springer
Цена: 8877 р.
Наличие на складе: Поставка под заказ.

Описание: The purpose of this book is to provide a careful and accessible account along modern lines of the subject which the title deals, as well as to discuss problems of current interest in the field. More precisely this book is devoted to the functional-analytic approach to a class of degenerate boundary value problems for second-order elliptic integro-differential operators which includes as particular cases the Dirichlet and Robin problems. This class of boundary value problems provides a new example of analytic semigroups. As an application, we construct a strong Markov process corresponding to such a diffusion phenomenon that a Markovian particle moves both by jumps and continuously in the state space until it dies at the time when it reaches the set where the particle is definitely absorbed.

An Introduction to Markov Processes

Автор: Stroock Daniel W.
Название: An Introduction to Markov Processes
ISBN: 3540234993 ISBN-13(EAN): 9783540234999
Издательство: Springer
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Цена: 7310 р.
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Описание: This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes. A whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium.


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