Author: N. V. Krylov
Publisher: Springer Science & Business Media
ISBN: 3540709142
Category : Science
Languages : en
Pages : 314
Book Description
Stochastic control theory is a relatively young branch of mathematics. The beginning of its intensive development falls in the late 1950s and early 1960s. ~urin~ that period an extensive literature appeared on optimal stochastic control using the quadratic performance criterion (see references in Wonham [76]). At the same time, Girsanov [25] and Howard [26] made the first steps in constructing a general theory, based on Bellman's technique of dynamic programming, developed by him somewhat earlier [4]. Two types of engineering problems engendered two different parts of stochastic control theory. Problems of the first type are associated with multistep decision making in discrete time, and are treated in the theory of discrete stochastic dynamic programming. For more on this theory, we note in addition to the work of Howard and Bellman, mentioned above, the books by Derman [8], Mine and Osaki [55], and Dynkin and Yushkevich [12]. Another class of engineering problems which encouraged the development of the theory of stochastic control involves time continuous control of a dynamic system in the presence of random noise. The case where the system is described by a differential equation and the noise is modeled as a time continuous random process is the core of the optimal control theory of diffusion processes. This book deals with this latter theory.
Controlled Diffusion Processes
Author: N. V. Krylov
Publisher: Springer Science & Business Media
ISBN: 3540709142
Category : Science
Languages : en
Pages : 314
Book Description
Stochastic control theory is a relatively young branch of mathematics. The beginning of its intensive development falls in the late 1950s and early 1960s. ~urin~ that period an extensive literature appeared on optimal stochastic control using the quadratic performance criterion (see references in Wonham [76]). At the same time, Girsanov [25] and Howard [26] made the first steps in constructing a general theory, based on Bellman's technique of dynamic programming, developed by him somewhat earlier [4]. Two types of engineering problems engendered two different parts of stochastic control theory. Problems of the first type are associated with multistep decision making in discrete time, and are treated in the theory of discrete stochastic dynamic programming. For more on this theory, we note in addition to the work of Howard and Bellman, mentioned above, the books by Derman [8], Mine and Osaki [55], and Dynkin and Yushkevich [12]. Another class of engineering problems which encouraged the development of the theory of stochastic control involves time continuous control of a dynamic system in the presence of random noise. The case where the system is described by a differential equation and the noise is modeled as a time continuous random process is the core of the optimal control theory of diffusion processes. This book deals with this latter theory.
Publisher: Springer Science & Business Media
ISBN: 3540709142
Category : Science
Languages : en
Pages : 314
Book Description
Stochastic control theory is a relatively young branch of mathematics. The beginning of its intensive development falls in the late 1950s and early 1960s. ~urin~ that period an extensive literature appeared on optimal stochastic control using the quadratic performance criterion (see references in Wonham [76]). At the same time, Girsanov [25] and Howard [26] made the first steps in constructing a general theory, based on Bellman's technique of dynamic programming, developed by him somewhat earlier [4]. Two types of engineering problems engendered two different parts of stochastic control theory. Problems of the first type are associated with multistep decision making in discrete time, and are treated in the theory of discrete stochastic dynamic programming. For more on this theory, we note in addition to the work of Howard and Bellman, mentioned above, the books by Derman [8], Mine and Osaki [55], and Dynkin and Yushkevich [12]. Another class of engineering problems which encouraged the development of the theory of stochastic control involves time continuous control of a dynamic system in the presence of random noise. The case where the system is described by a differential equation and the noise is modeled as a time continuous random process is the core of the optimal control theory of diffusion processes. This book deals with this latter theory.
Ergodic Control of Diffusion Processes
Author: Ari Arapostathis
Publisher: Cambridge University Press
ISBN: 0521768403
Category : Mathematics
Languages : en
Pages : 341
Book Description
The first comprehensive account of controlled diffusions with a focus on ergodic or 'long run average' control.
Publisher: Cambridge University Press
ISBN: 0521768403
Category : Mathematics
Languages : en
Pages : 341
Book Description
The first comprehensive account of controlled diffusions with a focus on ergodic or 'long run average' control.
Diffusion in Solids
Author: Helmut Mehrer
Publisher: Springer Science & Business Media
ISBN: 354071488X
Category : Technology & Engineering
Languages : en
Pages : 645
Book Description
This book describes the central aspects of diffusion in solids, and goes on to provide easy access to important information about diffusion in metals, alloys, semiconductors, ion-conducting materials, glasses and nanomaterials. Coverage includes diffusion-controlled phenomena including ionic conduction, grain-boundary and dislocation pipe diffusion. This book will benefit graduate students in such disciplines as solid-state physics, physical metallurgy, materials science, and geophysics, as well as scientists in academic and industrial research laboratories.
Publisher: Springer Science & Business Media
ISBN: 354071488X
Category : Technology & Engineering
Languages : en
Pages : 645
Book Description
This book describes the central aspects of diffusion in solids, and goes on to provide easy access to important information about diffusion in metals, alloys, semiconductors, ion-conducting materials, glasses and nanomaterials. Coverage includes diffusion-controlled phenomena including ionic conduction, grain-boundary and dislocation pipe diffusion. This book will benefit graduate students in such disciplines as solid-state physics, physical metallurgy, materials science, and geophysics, as well as scientists in academic and industrial research laboratories.
Controlled Markov Processes and Viscosity Solutions
Author: Wendell H. Fleming
Publisher: Springer Science & Business Media
ISBN: 0387310711
Category : Mathematics
Languages : en
Pages : 436
Book Description
This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It covers dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. New chapters in this second edition introduce the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets and two-controller, zero-sum differential games.
Publisher: Springer Science & Business Media
ISBN: 0387310711
Category : Mathematics
Languages : en
Pages : 436
Book Description
This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It covers dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. New chapters in this second edition introduce the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets and two-controller, zero-sum differential games.
Diffusion Processes and their Sample Paths
Author: Kiyosi Itô
Publisher: Springer Science & Business Media
ISBN: 3642620256
Category : Mathematics
Languages : en
Pages : 341
Book Description
Since its first publication in 1965 in the series Grundlehren der mathematischen Wissenschaften this book has had a profound and enduring influence on research into the stochastic processes associated with diffusion phenomena. Generations of mathematicians have appreciated the clarity of the descriptions given of one- or more- dimensional diffusion processes and the mathematical insight provided into Brownian motion. Now, with its republication in the Classics in Mathematics it is hoped that a new generation will be able to enjoy the classic text of Itô and McKean.
Publisher: Springer Science & Business Media
ISBN: 3642620256
Category : Mathematics
Languages : en
Pages : 341
Book Description
Since its first publication in 1965 in the series Grundlehren der mathematischen Wissenschaften this book has had a profound and enduring influence on research into the stochastic processes associated with diffusion phenomena. Generations of mathematicians have appreciated the clarity of the descriptions given of one- or more- dimensional diffusion processes and the mathematical insight provided into Brownian motion. Now, with its republication in the Classics in Mathematics it is hoped that a new generation will be able to enjoy the classic text of Itô and McKean.
Stochastic Modelling of Reaction–Diffusion Processes
Author: Radek Erban
Publisher: Cambridge University Press
ISBN: 1108572995
Category : Mathematics
Languages : en
Pages : 322
Book Description
This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. New mathematical approaches are explained using simple examples of biological models, which range in size from simulations of small biomolecules to groups of animals. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based (lattice-based) models.
Publisher: Cambridge University Press
ISBN: 1108572995
Category : Mathematics
Languages : en
Pages : 322
Book Description
This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. New mathematical approaches are explained using simple examples of biological models, which range in size from simulations of small biomolecules to groups of animals. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based (lattice-based) models.
Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems
Author: Xi-Ren Cao
Publisher: Springer Nature
ISBN: 3030418464
Category : Technology & Engineering
Languages : en
Pages : 376
Book Description
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.
Publisher: Springer Nature
ISBN: 3030418464
Category : Technology & Engineering
Languages : en
Pages : 376
Book Description
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.
Deterministic and Stochastic Optimal Control
Author: Wendell H. Fleming
Publisher: Springer Science & Business Media
ISBN: 1461263808
Category : Mathematics
Languages : en
Pages : 231
Book Description
This book may be regarded as consisting of two parts. In Chapters I-IV we pre sent what we regard as essential topics in an introduction to deterministic optimal control theory. This material has been used by the authors for one semester graduate-level courses at Brown University and the University of Kentucky. The simplest problem in calculus of variations is taken as the point of departure, in Chapter I. Chapters II, III, and IV deal with necessary conditions for an opti mum, existence and regularity theorems for optimal controls, and the method of dynamic programming. The beginning reader may find it useful first to learn the main results, corollaries, and examples. These tend to be found in the earlier parts of each chapter. We have deliberately postponed some difficult technical proofs to later parts of these chapters. In the second part of the book we give an introduction to stochastic optimal control for Markov diffusion processes. Our treatment follows the dynamic pro gramming method, and depends on the intimate relationship between second order partial differential equations of parabolic type and stochastic differential equations. This relationship is reviewed in Chapter V, which may be read inde pendently of Chapters I-IV. Chapter VI is based to a considerable extent on the authors' work in stochastic control since 1961. It also includes two other topics important for applications, namely, the solution to the stochastic linear regulator and the separation principle.
Publisher: Springer Science & Business Media
ISBN: 1461263808
Category : Mathematics
Languages : en
Pages : 231
Book Description
This book may be regarded as consisting of two parts. In Chapters I-IV we pre sent what we regard as essential topics in an introduction to deterministic optimal control theory. This material has been used by the authors for one semester graduate-level courses at Brown University and the University of Kentucky. The simplest problem in calculus of variations is taken as the point of departure, in Chapter I. Chapters II, III, and IV deal with necessary conditions for an opti mum, existence and regularity theorems for optimal controls, and the method of dynamic programming. The beginning reader may find it useful first to learn the main results, corollaries, and examples. These tend to be found in the earlier parts of each chapter. We have deliberately postponed some difficult technical proofs to later parts of these chapters. In the second part of the book we give an introduction to stochastic optimal control for Markov diffusion processes. Our treatment follows the dynamic pro gramming method, and depends on the intimate relationship between second order partial differential equations of parabolic type and stochastic differential equations. This relationship is reviewed in Chapter V, which may be read inde pendently of Chapters I-IV. Chapter VI is based to a considerable extent on the authors' work in stochastic control since 1961. It also includes two other topics important for applications, namely, the solution to the stochastic linear regulator and the separation principle.
Optimal Control of Diffusion Processes
Author: Vivek S. Borkar
Publisher: Longman
ISBN:
Category : Control theory
Languages : en
Pages : 212
Book Description
Publisher: Longman
ISBN:
Category : Control theory
Languages : en
Pages : 212
Book Description
Modern Aspects of Diffusion-Controlled Reactions
Author: E. Kotomin
Publisher: Elsevier
ISBN: 0080536670
Category : Science
Languages : en
Pages : 637
Book Description
This monograph deals with the effects of reactant spatial correlations arising in the course of basic bimolecular reactions describing defect recombination, energy transfer and exciton annihilation in condensed matter. These effects lead to the kinetics considered abnormal from the standard chemical kinetics point of view. Numerous bimolecular reaction regimes and conditions are analysed in detail. Special attention is paid to the development and numerous applications of a novel, many-point density (MPD) formalism, which is based on Kirkwood's superposition approximation used for decoupling three-particle correlation functions.The book demonstrates that incorporation of the reaction-induced spatial correlations of similar reactants (e.g., vacancy-vacancy) leads to the development of an essentially non-Poisson spectrum of reactant density fluctuations. This can completely change the kinetics at longer times since it no longer obeys the law of mass action. The language of the correlation lengths and critical exponents similar to physics of critical phenomena is used instead. A relation between MPD theory and synergistics is discussed. The validity of the theorem giving a critical complexity for the two-step reactions exhibiting self-organization phenomena is questioned. Theoretical results are illustrated by numerous experimental data.
Publisher: Elsevier
ISBN: 0080536670
Category : Science
Languages : en
Pages : 637
Book Description
This monograph deals with the effects of reactant spatial correlations arising in the course of basic bimolecular reactions describing defect recombination, energy transfer and exciton annihilation in condensed matter. These effects lead to the kinetics considered abnormal from the standard chemical kinetics point of view. Numerous bimolecular reaction regimes and conditions are analysed in detail. Special attention is paid to the development and numerous applications of a novel, many-point density (MPD) formalism, which is based on Kirkwood's superposition approximation used for decoupling three-particle correlation functions.The book demonstrates that incorporation of the reaction-induced spatial correlations of similar reactants (e.g., vacancy-vacancy) leads to the development of an essentially non-Poisson spectrum of reactant density fluctuations. This can completely change the kinetics at longer times since it no longer obeys the law of mass action. The language of the correlation lengths and critical exponents similar to physics of critical phenomena is used instead. A relation between MPD theory and synergistics is discussed. The validity of the theorem giving a critical complexity for the two-step reactions exhibiting self-organization phenomena is questioned. Theoretical results are illustrated by numerous experimental data.