Modern Trends in Controlled Stochastic Processes:

Modern Trends in Controlled Stochastic Processes:
Author: Alexey Piunovskiy
Publisher: Springer Nature
Total Pages: 356
Release: 2021-06-04
Genre: Technology & Engineering
ISBN: 3030769283
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This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. ​

Modern Trends in Controlled Stochastic Processes

Modern Trends in Controlled Stochastic Processes
Author: Alexey B. Piunovskiy
Publisher: Luniver Press
Total Pages: 342
Release: 2010-09
Genre: Mathematics
ISBN: 1905986300
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World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, controlled diffusions, piece-wise deterministic processes etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several numerical methods, index-based approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization and Information Transmission. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.

Modern Trends in Controlled Stochastic Processes: Theory and Applications

Modern Trends in Controlled Stochastic Processes: Theory and Applications
Author: Alexey Piunovskiy
Publisher: Luniver Press
Total Pages: 322
Release: 2015-12-15
Genre: Mathematics
ISBN: 9781905986453
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World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, Controlled Diffusions, etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several Approximate and Numerical Methods, Index-Based Approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization, Control of Water Resources, Information Transmission, Quality Control, Pollution Control and so on. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.

Controlled Stochastic Processes

Controlled Stochastic Processes
Author: I. I. Gihman
Publisher: Springer Science & Business Media
Total Pages: 242
Release: 2012-12-06
Genre: Mathematics
ISBN: 146126202X
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The theory of controlled processes is one of the most recent mathematical theories to show very important applications in modern engineering, parti cularly for constructing automatic control systems, as well as for problems of economic control. However, actual systems subject to control do not admit a strictly deterministic analysis in view of random factors of various kinds which influence their behavior. Such factors include, for example, random noise occurring in the electrical system, variations in the supply and demand of commodities, fluctuations in the labor force in economics, and random failures of components on an automated line. The theory of con trolled processes takes the random nature of the behavior of a system into account. In such cases it is natural, when choosing a control strategy, to proceed from the average expected result, taking note of all the possible variants of the behavior of a controlled system. An extensive literature is devoted to various economic and engineering systems of control (some of these works are listed in the Bibliography). is no text which adequately covers the general However, as of now there mathematical theory of controlled processes. The authors ofthis monograph have attempted to fill this gap. In this volume the general theory of discrete-parameter (time) controlled processes (Chapter 1) and those with continuous-time (Chapter 2), as well as the theory of controlled stochastic differential equations (Chapter 3), are presented.

Optimization, Control, and Applications of Stochastic Systems

Optimization, Control, and Applications of Stochastic Systems
Author: Daniel Hernández-Hernández
Publisher: Springer Science & Business Media
Total Pages: 331
Release: 2012-08-15
Genre: Science
ISBN: 0817683372
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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.

Stochastic Analysis, Filtering, and Stochastic Optimization

Stochastic Analysis, Filtering, and Stochastic Optimization
Author: George Yin
Publisher: Springer Nature
Total Pages: 466
Release: 2022-04-22
Genre: Mathematics
ISBN: 3030985199
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This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic Processes, Filtering, and Stochastic Optimization spans more than five decades. Invited authors include his dissertation advisor, past collaborators, colleagues, mentees, and graduate students of Professor Davis, as well as scholars who have worked in the above areas. Their contributions may expand upon topics in piecewise deterministic processes, pathwise stochastic calculus, martingale methods in stochastic optimization, filtering, mean-field games, time-inconsistency, as well as impulse, singular, risk-sensitive and robust stochastic control.

Controlled Stochastic Processes

Controlled Stochastic Processes
Author: Iosif Ilʹich Gikhman
Publisher:
Total Pages: 237
Release: 1979
Genre: Control theory
ISBN: 9783540904106
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Selected Topics on Continuous-time Controlled Markov Chains and Markov Games

Selected Topics on Continuous-time Controlled Markov Chains and Markov Games
Author: Tomas Prieto-Rumeau
Publisher: World Scientific
Total Pages: 292
Release: 2012
Genre: Mathematics
ISBN: 1848168497
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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.

Continuous-Time Markov Decision Processes

Continuous-Time Markov Decision Processes
Author: Alexey Piunovskiy
Publisher: Springer Nature
Total Pages: 605
Release: 2020-11-09
Genre: Mathematics
ISBN: 3030549879
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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.

Markov Decision Processes with Applications to Finance

Markov Decision Processes with Applications to Finance
Author: Nicole Bäuerle
Publisher: Springer Science & Business Media
Total Pages: 393
Release: 2011-06-06
Genre: Mathematics
ISBN: 3642183247
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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).