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Finite Stage Continuous Time Markov Decision Processes With An Infinite Planning Horizon
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Book Synopsis Continuous-Time Markov Decision Processes by : Xianping Guo
Download or read book Continuous-Time Markov Decision Processes written by Xianping Guo and published by Springer Science & Business Media. This book was released on 2009-09-18 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained presentation of recent developments on the theory and applications of continuous-time MDPs. The MDPs in this volume include most of the cases that arise in applications, because they allow unbounded transition and reward/cost rates. Much of the material appears for the first time in book form.
Book Synopsis Continuous-Time Markov Decision Processes by : Alexey Piunovskiy
Download or read book Continuous-Time Markov Decision Processes written by Alexey Piunovskiy and published by Springer Nature. This book was released on 2020-11-09 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.
Book Synopsis Markov Decision Processes by : Martin L. Puterman
Download or read book Markov Decision Processes written by Martin L. Puterman and published by John Wiley & Sons. This book was released on 2014-08-28 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 treatment of theoretical and computational aspects of discrete-time Markov decision processes." —Journal of the American Statistical Association
Book Synopsis Finite State Continuous-time Markov Decision Processes, with Applications to a Class of Optimization Problems in Queueing Theory by : Bruce L. Miller
Download or read book Finite State Continuous-time Markov Decision Processes, with Applications to a Class of Optimization Problems in Queueing Theory written by Bruce L. Miller and published by . This book was released on 1967 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Selected Topics on Continuous-time Controlled Markov Chains and Markov Games by : Tomas Prieto-Rumeau
Download or read book Selected Topics on Continuous-time Controlled Markov Chains and Markov Games written by Tomas Prieto-Rumeau and published by World Scientific. This book was released on 2012 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes. They form a class of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with Markov games, where two decision-makers (or players) try to optimize their own objective function. Both decision-making processes appear in a large number of applications in economics, operations research, engineering, and computer science, among other areas. An extensive, self-contained, up-to-date analysis of basic optimality criteria (such as discounted and average reward), and advanced optimality criteria (e.g., bias, overtaking, sensitive discount, and Blackwell optimality) is presented. A particular emphasis is made on the application of the results herein: algorithmic and computational issues are discussed, and applications to population models and epidemic processes are shown. This book is addressed to students and researchers in the fields of stochastic control and stochastic games. Moreover, it could be of interest also to undergraduate and beginning graduate students because the reader is not supposed to have a high mathematical background: a working knowledge of calculus, linear algebra, probability, and continuous-time Markov chains should suffice to understand the contents of the book.
Book Synopsis Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems by : Xi-Ren Cao
Download or read book Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems written by Xi-Ren Cao and published by Springer Nature. This book was released on 2020-05-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph applies the relative optimization approach to time nonhomogeneous continuous-time and continuous-state dynamic systems. The approach is intuitively clear and does not require deep knowledge of the mathematics of partial differential equations. The topics covered have the following distinguishing features: long-run average with no under-selectivity, non-smooth value functions with no viscosity solutions, diffusion processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming. The book begins with an introduction to relative optimization, including a comparison with the traditional approach of dynamic programming. The text then studies the Markov process, focusing on infinite-horizon optimization problems, and moves on to discuss optimal control of diffusion processes with semi-smooth value functions and degenerate points, and optimization of multi-dimensional diffusion processes. The book concludes with a brief overview of performance derivative-based optimization. Among the more important novel considerations presented are: the extension of the Hamilton–Jacobi–Bellman optimality condition from smooth to semi-smooth value functions by derivation of explicit optimality conditions at semi-smooth points and application of this result to degenerate and reflected processes; proof of semi-smoothness of the value function at degenerate points; attention to the under-selectivity issue for the long-run average and bias optimality; discussion of state classification for time nonhomogeneous continuous processes and multi-class optimization; and development of the multi-dimensional Tanaka formula for semi-smooth functions and application of this formula to stochastic control of multi-dimensional systems with degenerate points. The book will be of interest to researchers and students in the field of stochastic control and performance optimization alike.
Download or read book Technical Abstract Bulletin written by and published by . This book was released on with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis OPTIMIZATION AND OPERATIONS RESEARCH – Volume IV by : Ulrich Derigs
Download or read book OPTIMIZATION AND OPERATIONS RESEARCH – Volume IV written by Ulrich Derigs and published by EOLSS Publications. This book was released on 2009-04-15 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization and Operations Research is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The Theme on Optimization and Operations Research is organized into six different topics which represent the main scientific areas of the theme: 1. Fundamentals of Operations Research; 2. Advanced Deterministic Operations Research; 3. Optimization in Infinite Dimensions; 4. Game Theory; 5. Stochastic Operations Research; 6. Decision Analysis, which are then expanded into multiple subtopics, each as a chapter. These four volumes are aimed at the following five major target audiences: University and College students Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers and NGOs.
Author :Daniel Hernández-Hernández Publisher :Springer Science & Business Media ISBN 13 :0817683372 Total Pages :331 pages Book Rating :4.8/5 (176 download)
Book Synopsis Optimization, Control, and Applications of Stochastic Systems by : Daniel Hernández-Hernández
Download or read book Optimization, Control, and Applications of Stochastic Systems written by Daniel Hernández-Hernández and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields. Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.
Book Synopsis Operations Research: Algorithms And Applications by : Rathindra P. Sen
Download or read book Operations Research: Algorithms And Applications written by Rathindra P. Sen and published by PHI Learning Pvt. Ltd.. This book was released on 2010-01-30 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: It covers all the relevant topics along with the recent developments in the field. The book begins with an overview of operations research and then discusses the simplex method of optimization and duality concept along with the deterministic models such as post-optimality analysis, transportation and assignment models. While covering hybrid models of operations research, the book elaborates PERT (Programme Evaluation and Review Technique), CPM (Critical Path Method), dynamic programming, inventory control models, simulation techniques and their applications in mathematical modelling and computer programming. It explains the decision theory, game theory, queueing theory, sequencing models, replacement and reliability problems, information theory and Markov processes which are related to stochastic models. Finally, this well-organized book describes advanced deterministic models that include goal programming, integer programming and non-linear programming.
Book Synopsis Stochastic Models in Operations Research: Stochastic optimization by : Daniel P. Heyman
Download or read book Stochastic Models in Operations Research: Stochastic optimization written by Daniel P. Heyman and published by Courier Corporation. This book was released on 2004-01-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate treatments: stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, they emphasize the practical importance, intellectual stimulation, and mathematical elegance of stochastic models and are intended primarily as graduate-level texts.
Book Synopsis Markov Decision Processes with Applications to Finance by : Nicole Bäuerle
Download or read book Markov Decision Processes with Applications to Finance written by Nicole Bäuerle and published by Springer Science & Business Media. This book was released on 2011-06-06 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers in both applied probability and finance, and provides exercises (without solutions).
Book Synopsis Government-wide Index to Federal Research & Development Reports by :
Download or read book Government-wide Index to Federal Research & Development Reports written by and published by . This book was released on 1967 with total page 1352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Markov Processes and Controlled Markov Chains by : Zhenting Hou
Download or read book Markov Processes and Controlled Markov Chains written by Zhenting Hou and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South American and Asian scholars.
Book Synopsis Markovian Decision Processes by : Hisashi Mine
Download or read book Markovian Decision Processes written by Hisashi Mine and published by Elsevier Publishing Company. This book was released on 1970 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markovian decision processes with discounting; Markovian decision processes with no discouting; Dynamic programming viewpoint of markovian decision processes; Semi-markovian decision processes; Generalized markovian decision processes; The principle of contraction mappings in markovian decision processes.
Book Synopsis Naval Research Logistics Quarterly by :
Download or read book Naval Research Logistics Quarterly written by and published by . This book was released on 1984 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Foundations of Non-stationary Dynamic Programming with Discrete Time Parameter by : K. Hinderer
Download or read book Foundations of Non-stationary Dynamic Programming with Discrete Time Parameter written by K. Hinderer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results.
