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
Описание: Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The bookexplains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models.The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory.
Автор: L. C. G. Rogers Название: Diffusions, Markov Processes and Martingales ISBN: 0521775930 ISBN-13(EAN): 9780521775939 Издательство: Cambridge Academ Рейтинг: Цена: 6901 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now available in paperback, this celebrated book has been prepared with readers’ needs in mind, remaining a systematic treatment of the subject whilst retaining its vitality. The second volume follows on from the first, concentrating on stochastic integrals, stochastic differential equations, excursion theory and the general theory of processes. Much effort has gone into making these subjects as accessible as possible by providing many concrete examples that illustrate techniques of calculation, and by treating all topics from the ground up, starting from simple cases. Many of the examples and proofs are new; some important calculational techniques appeared for the first time in this book. Together with its companion volume, this book helps equip graduate students for research into a subject of great intrinsic interest and wide application in physics, biology, engineering, finance and computer science.
Автор: Krishnamurthy Название: Partially Observed Markov Decision Processes ISBN: 1107134609 ISBN-13(EAN): 9781107134607 Издательство: Cambridge Academ Рейтинг: Цена: 8397 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covering formulation, algorithms, and structural results, and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. Bringing together research from across the literature, the book provides an introduction to nonlinear filtering followed by a systematic development of stochastic dynamic programming, lattice programming and reinforcement learning for POMDPs. Questions addressed in the book include: when does a POMDP have a threshold optimal policy? When are myopic policies optimal? How do local and global decision makers interact in adaptive decision making in multi-agent social learning where there is herding and data incest? And how can sophisticated radars and sensors adapt their sensing in real time?
Описание: Often, real-world problems modeled by Markov decision processes (MDPs) are difficult to solve in practise because of the curse of dimensionality. In others, explicit specification of the MDP model parameters is not feasible, but simulation samples are available. This book provides many specific algorithms, and illustrative numerical examples.
Описание: Presents an introduction to finite Markov chains and Markov decision processes, with applications in engineering and management. This book introduces discrete-time, finite-state Markov chains, and Markov decision processes. It describes both algorithms and applications, enabling students to understand the logical basis for the algorithms.
Автор: Guo Название: Continuous-Time Markov Decision Processes ISBN: 3642025463 ISBN-13(EAN): 9783642025464 Издательство: Springer Рейтинг: Цена: 10449 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A collection of papers on Markov random walks and Markov additive processes and their applications. It provides the foundations of these stochastic processes underpinned by a theoretical framework based on Semiregenerative phenomena.
Описание: Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science andengineering, the authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises with complete solutions, adapted to needs and skills of students. Following on from the success of Probability and Statistics by Example: Basic Probability and Statistics, the authors here concentrate on random processes, particularly Markov processes, emphasising modelsrather than general constructions. Basic mathematical facts are supplied as and when they are needed andhistorical information is sprinkled throughout.
Автор: Filar Название: Competitive Markov Decision Processes ISBN: 0387948058 ISBN-13(EAN): 9780387948058 Издательство: Springer Рейтинг: Цена: 14629 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Competitive Markov decision processes are examined from the standpoints of modelling and optimization in this text. Topics covered include mathematical programming, summable stochastic games, average-reward stochastic games, and applications and special classes of stochastic games.
Описание: The book presents a detailed mathematical introduction to the main classes of Markov processes together with their applications in various fields. It has been developed from a number of successful courses taught by the author to a wide-ranging student audience, including in Mathematicians, Engineers and Biologists.
Описание: This volume concentrates on how to construct a Markov process by starting with a suitable pseudo-differential operator. Feller processes, Hunt processes
associated with Lp-sub-Markovian semigroups and processes constructed by using the Martingale problem are at the center of the considerations. The potential theory of these
processes is further developed and applications are discussed.
Due to the non-locality of the generators, the processes are jump processes and their relations to Levy
processes are investigated. Special emphasis is given to the symbol of a process, a notion which generalizes that of the characteristic exponent of a Levy process and provides a
natural link to pseudo-differential operator theory.
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