Finite Approximations in Discrete-Time Stochastic Control

Finite Approximations in Discrete-Time Stochastic Control PDF Author: Naci Saldi
Publisher: Birkhäuser
ISBN: 3319790331
Category : Mathematics
Languages : en
Pages : 196

Get Book Here

Book Description
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.

Finite Approximations in Discrete-Time Stochastic Control

Finite Approximations in Discrete-Time Stochastic Control PDF Author: Naci Saldi
Publisher: Birkhäuser
ISBN: 3319790331
Category : Mathematics
Languages : en
Pages : 196

Get Book Here

Book Description
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.

Backward Stochastic Differential Equations

Backward Stochastic Differential Equations PDF Author: N El Karoui
Publisher: CRC Press
ISBN: 9780582307339
Category : Mathematics
Languages : en
Pages : 236

Get Book Here

Book Description
This book presents the texts of seminars presented during the years 1995 and 1996 at the Université Paris VI and is the first attempt to present a survey on this subject. Starting from the classical conditions for existence and unicity of a solution in the most simple case-which requires more than basic stochartic calculus-several refinements on the hypotheses are introduced to obtain more general results.

Neural Approximations for Optimal Control and Decision

Neural Approximations for Optimal Control and Decision PDF Author: Riccardo Zoppoli
Publisher: Springer Nature
ISBN: 3030296938
Category : Technology & Engineering
Languages : en
Pages : 532

Get Book Here

Book Description
Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc. Features of the text include: • a general functional optimization framework; • thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems; • comparison of classical and neural-network based methods of approximate solution; • bounds to the errors of approximate solutions; • solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several; • applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and • numerous, numerically detailed examples. The authors’ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.

Modern Trends in Controlled Stochastic Processes:

Modern Trends in Controlled Stochastic Processes: PDF Author: Alexey Piunovskiy
Publisher: Springer Nature
ISBN: 3030769283
Category : Technology & Engineering
Languages : en
Pages : 356

Get Book Here

Book Description
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. ​

From Shortest Paths to Reinforcement Learning

From Shortest Paths to Reinforcement Learning PDF Author: Paolo Brandimarte
Publisher: Springer Nature
ISBN: 3030618676
Category : Business & Economics
Languages : en
Pages : 216

Get Book Here

Book Description
Dynamic programming (DP) has a relevant history as a powerful and flexible optimization principle, but has a bad reputation as a computationally impractical tool. This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with DP and its potential applications, offering the possibility of actual experimentation and hands-on experience. The book assumes basic familiarity with probability and optimization, and is suitable to both practitioners and graduate students in engineering, applied mathematics, management, finance and economics.

Stochastic Teams, Games, and Control under Information Constraints

Stochastic Teams, Games, and Control under Information Constraints PDF Author: Serdar Yüksel
Publisher: Springer Nature
ISBN: 3031540719
Category :
Languages : en
Pages : 935

Get Book Here

Book Description


Control and System Theory of Discrete-Time Stochastic Systems

Control and System Theory of Discrete-Time Stochastic Systems PDF Author: Jan H. van Schuppen
Publisher: Springer Nature
ISBN: 3030669521
Category : Technology & Engineering
Languages : en
Pages : 940

Get Book Here

Book Description
This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems. Applications of the theory in the book include the control of ships, shock absorbers, traffic and communications networks, and power systems with fluctuating power flows. The focus of the book is a stochastic control system defined for a spectrum of probability distributions including Bernoulli, finite, Poisson, beta, gamma, and Gaussian distributions. The concepts of observability and controllability of a stochastic control system are defined and characterized. Each output process considered is, with respect to conditions, represented by a stochastic system called a stochastic realization. The existence of a control law is related to stochastic controllability while the existence of a filter system is related to stochastic observability. Stochastic control with partial observations is based on the existence of a stochastic realization of the filtration of the observed process.​

Modeling, Stochastic Control, Optimization, and Applications

Modeling, Stochastic Control, Optimization, and Applications PDF Author: George Yin
Publisher: Springer
ISBN: 3030254984
Category : Mathematics
Languages : en
Pages : 593

Get Book Here

Book Description
This volume collects papers, based on invited talks given at the IMA workshop in Modeling, Stochastic Control, Optimization, and Related Applications, held at the Institute for Mathematics and Its Applications, University of Minnesota, during May and June, 2018. There were four week-long workshops during the conference. They are (1) stochastic control, computation methods, and applications, (2) queueing theory and networked systems, (3) ecological and biological applications, and (4) finance and economics applications. For broader impacts, researchers from different fields covering both theoretically oriented and application intensive areas were invited to participate in the conference. It brought together researchers from multi-disciplinary communities in applied mathematics, applied probability, engineering, biology, ecology, and networked science, to review, and substantially update most recent progress. As an archive, this volume presents some of the highlights of the workshops, and collect papers covering a broad range of topics.

Privacy in Dynamical Systems

Privacy in Dynamical Systems PDF Author: Farhad Farokhi
Publisher: Springer Nature
ISBN: 9811504938
Category : Technology & Engineering
Languages : en
Pages : 290

Get Book Here

Book Description
This book addresses privacy in dynamical systems, with applications to smart metering, traffic estimation, and building management. In the first part, the book explores statistical methods for privacy preservation from the areas of differential privacy and information-theoretic privacy (e.g., using privacy metrics motivated by mutual information, relative entropy, and Fisher information) with provable guarantees. In the second part, it investigates the use of homomorphic encryption for the implementation of control laws over encrypted numbers to support the development of fully secure remote estimation and control. Chiefly intended for graduate students and researchers, the book provides an essential overview of the latest developments in privacy-aware design for dynamical systems.

Managerial Planning

Managerial Planning PDF Author: Charles S. Tapiero
Publisher: Routledge
ISBN: 1351243209
Category : Business & Economics
Languages : en
Pages : 410

Get Book Here

Book Description
Originally published in 1977. Management is a dynamic process reflected in three essential functions: management of time, change and people. The book provides a bridging gap between quantitative theories imbedded in the systems approach and managerial decision-making over time and under risk. The conventional wisdom that management is a dynamic process is rendered operational. This title will be of interest to students of business studies and management.