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Dynamic Programming and Optimal Control

Dynamic Programming and Optimal Control Author Dimitri P. Bertsekas
ISBN-10 1886529086
Release 2017
Pages
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Dynamic Programming and Optimal Control has been writing in one form or another for most of life. You can find so many inspiration from Dynamic Programming and Optimal Control also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Dynamic Programming and Optimal Control book for free.



Dynamic Programming and Optimal Control

Dynamic Programming and Optimal Control Author Dimitri P. Bertsekas
ISBN-10 1886529086
Release 1995
Pages 445
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Dynamic Programming and Optimal Control has been writing in one form or another for most of life. You can find so many inspiration from Dynamic Programming and Optimal Control also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Dynamic Programming and Optimal Control book for free.



Approximate Dynamic Programming

Approximate Dynamic Programming Author Warren B. Powell
ISBN-10 0470182954
Release 2007-10-05
Pages 480
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Approximate Dynamic Programming has been writing in one form or another for most of life. You can find so many inspiration from Approximate Dynamic Programming also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Approximate Dynamic Programming book for free.



Introduction to Stochastic Dynamic Programming

Introduction to Stochastic Dynamic Programming Author Sheldon M. Ross
ISBN-10 9781483269092
Release 2014-07-10
Pages 178
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Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist—providing counterexamples where appropriate—and then presents methods for obtaining such policies when they do. In addition, general areas of application are presented. The final two chapters are concerned with more specialized models. These include stochastic scheduling models and a type of process known as a multiproject bandit. The mathematical prerequisites for this text are relatively few. No prior knowledge of dynamic programming is assumed and only a moderate familiarity with probability— including the use of conditional expectation—is necessary.



Abstract Dynamic Programming

Abstract Dynamic Programming Author Dimitri P. Bertsekas
ISBN-10 1886529426
Release 2013-04-30
Pages 248
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Abstract Dynamic Programming has been writing in one form or another for most of life. You can find so many inspiration from Abstract Dynamic Programming also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Abstract Dynamic Programming book for free.



Optimal Control and Viscosity Solutions of Hamilton Jacobi Bellman Equations

Optimal Control and Viscosity Solutions of Hamilton Jacobi Bellman Equations Author Martino Bardi
ISBN-10 9780817647551
Release 2009-05-21
Pages 574
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This softcover book is a self-contained account of the theory of viscosity solutions for first-order partial differential equations of Hamilton–Jacobi type and its interplay with Bellman’s dynamic programming approach to optimal control and differential games. It will be of interest to scientists involved in the theory of optimal control of deterministic linear and nonlinear systems. The work may be used by graduate students and researchers in control theory both as an introductory textbook and as an up-to-date reference book.



Dynamic Programming

Dynamic Programming Author Richard Bellman
ISBN-10 9780486317199
Release 2013-04-09
Pages 366
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Introduction to mathematical theory of multistage decision processes takes a "functional equation" approach. Topics include existence and uniqueness theorems, optimal inventory equation, bottleneck problems, multistage games, Markovian decision processes, and more. 1957 edition.



Dynamic Programming

Dynamic Programming Author Moshe Sniedovich
ISBN-10 1420014633
Release 2010-09-10
Pages 624
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Incorporating a number of the author’s recent ideas and examples, Dynamic Programming: Foundations and Principles, Second Edition presents a comprehensive and rigorous treatment of dynamic programming. The author emphasizes the crucial role that modeling plays in understanding this area. He also shows how Dijkstra’s algorithm is an excellent example of a dynamic programming algorithm, despite the impression given by the computer science literature. New to the Second Edition Expanded discussions of sequential decision models and the role of the state variable in modeling A new chapter on forward dynamic programming models A new chapter on the Push method that gives a dynamic programming perspective on Dijkstra’s algorithm for the shortest path problem A new appendix on the Corridor method Taking into account recent developments in dynamic programming, this edition continues to provide a systematic, formal outline of Bellman’s approach to dynamic programming. It looks at dynamic programming as a problem-solving methodology, identifying its constituent components and explaining its theoretical basis for tackling problems.



Dynamic Programming and Its Application to Optimal Control

Dynamic Programming and Its Application to Optimal Control Author
ISBN-10 0080955894
Release 1971-10-11
Pages 322
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In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering



Dynamic Programming

Dynamic Programming Author Eric V. Denardo
ISBN-10 9780486150857
Release 2012-12-27
Pages 240
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Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.



Dynamic Programming

Dynamic Programming Author Dimitri P. Bertsekas
ISBN-10 0132215810
Release 1987-01-01
Pages 376
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Dynamic Programming has been writing in one form or another for most of life. You can find so many inspiration from Dynamic Programming also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Dynamic Programming book for free.



Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control Author Frank L. Lewis
ISBN-10 9781118453971
Release 2013-01-28
Pages 648
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Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.



Applied Dynamic Programming

Applied Dynamic Programming Author Richard E. Bellman
ISBN-10 9781400874651
Release 2015-12-08
Pages 390
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This comprehensive study of dynamic programming applied to numerical solution of optimization problems. It will interest aerodynamic, control, and industrial engineers, numerical analysts, and computer specialists, applied mathematicians, economists, and operations and systems analysts. Originally published in 1962. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.



Linear Network Optimization

Linear Network Optimization Author Dimitri P. Bertsekas
ISBN-10 0262023342
Release 1991
Pages 359
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Large-scale optimization is becoming increasingly important for students and professionals in electrical and industrial engineering, computer science, management science and operations research, and applied mathematics. Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems. It is the first text to clearly explain important recent algorithms such as auction and relaxation, proposed by the author and others for the solution of these problems. Its coverage of both theory and implementations make it particularly useful as a text for a graduate-level course on network optimization as well as a practical guide to state-of-the-art codes in the field. Bertsekas focuses on the algorithms that have proved successful in practice and provides FORTRAN codes that implement them. The presentation is clear, mathematically rigorous, and economical. Many illustrations, examples, and exercises are included in the text. Dimitri P. Bertsekas is Professor of Electrical Engineering and Computer Science at MIT. Contents: Introduction. Simplex Methods. Dual Ascent Methods. Auction Algorithms. Performance and Comparisons. Appendixes.



Stochastic Systems

Stochastic Systems Author P. R. Kumar
ISBN-10 9781611974256
Release 2015-12-15
Pages 358
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Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.



Optimal Learning

Optimal Learning Author Warren B. Powell
ISBN-10 9781118309841
Release 2013-07-09
Pages 404
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Learn the science of collecting information to make effective decisions Everyday decisions are made without the benefit of accurate information. Optimal Learning develops the needed principles for gathering information to make decisions, especially when collecting information is time-consuming and expensive. Designed for readers with an elementary background in probability and statistics, the book presents effective and practical policies illustrated in a wide range of applications, from energy, homeland security, and transportation to engineering, health, and business. This book covers the fundamental dimensions of a learning problem and presents a simple method for testing and comparing policies for learning. Special attention is given to the knowledge gradient policy and its use with a wide range of belief models, including lookup table and parametric and for online and offline problems. Three sections develop ideas with increasing levels of sophistication: Fundamentals explores fundamental topics, including adaptive learning, ranking and selection, the knowledge gradient, and bandit problems Extensions and Applications features coverage of linear belief models, subset selection models, scalar function optimization, optimal bidding, and stopping problems Advanced Topics explores complex methods including simulation optimization, active learning in mathematical programming, and optimal continuous measurements Each chapter identifies a specific learning problem, presents the related, practical algorithms for implementation, and concludes with numerous exercises. A related website features additional applications and downloadable software, including MATLAB and the Optimal Learning Calculator, a spreadsheet-based package that provides an introduc­tion to learning and a variety of policies for learning.



Dynamic Optimization Second Edition

Dynamic Optimization  Second Edition Author Morton I. Kamien
ISBN-10 9780486310282
Release 2013-04-17
Pages 400
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Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.