## Dynamic Programming

**Author**: Richard Bellman

**Publisher:**Courier Corporation

**ISBN:**0486317196

**Category:**Mathematics

**Page:**366

**View:**4938

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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

*A Computational Tool*

**Author**: Art Lew,Holger Mauch

**Publisher:**Springer Science & Business Media

**ISBN:**3540370137

**Category:**Computers

**Page:**379

**View:**6461

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This book provides a practical introduction to computationally solving discrete optimization problems using dynamic programming. From the examples presented, readers should more easily be able to formulate dynamic programming solutions to their own problems of interest. We also provide and describe the design, implementation, and use of a software tool that has been used to numerically solve all of the problems presented earlier in the book.

## Dynamic Programming

*Foundations and Principles, Second Edition*

**Author**: Moshe Sniedovich

**Publisher:**CRC Press

**ISBN:**9781420014631

**Category:**Business & Economics

**Page:**624

**View:**1959

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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.

## Iterative Dynamic Programming

**Author**: Rein Luus

**Publisher:**CRC Press

**ISBN:**9781420036022

**Category:**Mathematics

**Page:**344

**View:**2211

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Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving problems of very low dimension. To overcome these limitations, author Rein Luus suggested using it in an iterative fashion. Although this method required vast computer resources, modifications to his original scheme have made the computational procedure feasible. With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions. Iterative Dynamic Programming offers a comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others - previously available only in scattered journal articles - along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.

## Dynamic Programming

*Models and Applications*

**Author**: Eric V. Denardo

**Publisher:**Courier Corporation

**ISBN:**0486150852

**Category:**Technology & Engineering

**Page:**240

**View:**1075

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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.

## Differential Dynamic Programming

**Author**: David H. Jacobson,David Q. Mayne

**Publisher:**Elsevier Publishing Company

**ISBN:**N.A

**Category:**Control theory

**Page:**208

**View:**584

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## Pyramid Algorithms

*A Dynamic Programming Approach to Curves and Surfaces for Geometric Modeling*

**Author**: Ron Goldman

**Publisher:**Elsevier

**ISBN:**9780080515472

**Category:**Computers

**Page:**576

**View:**1314

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Pyramid Algorithms presents a unique approach to understanding, analyzing, and computing the most common polynomial and spline curve and surface schemes used in computer-aided geometric design, employing a dynamic programming method based on recursive pyramids. The recursive pyramid approach offers the distinct advantage of revealing the entire structure of algorithms, as well as relationships between them, at a glance. This book-the only one built around this approach-is certain to change the way you think about CAGD and the way you perform it, and all it requires is a basic background in calculus and linear algebra, and simple programming skills. * Written by one of the world's most eminent CAGD researchers * Designed for use as both a professional reference and a textbook, and addressed to computer scientists, engineers, mathematicians, theoreticians, and students alike * Includes chapters on Bezier curves and surfaces, B-splines, blossoming, and multi-sided Bezier patches * Relies on an easily understood notation, and concludes each section with both practical and theoretical exercises that enhance and elaborate upon the discussion in the text * Foreword by Professor Helmut Pottmann, Vienna University of Technology

## Handbook of Learning and Approximate Dynamic Programming

**Author**: Jennie Si,Andrew G. Barto,Warren B. Powell,Don Wunsch

**Publisher:**John Wiley & Sons

**ISBN:**9780471660545

**Category:**Technology & Engineering

**Page:**672

**View:**2511

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A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book Includes ideas, directions, and recent results on current research issues and addresses applications where ADP has been successfully implemented The contributors are leading researchers in the field

## Nonserial Dynamic Programming

**Author**: Bertele?

**Publisher:**Academic Press

**ISBN:**0080956009

**Category:**Computers

**Page:**234

**View:**6116

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Nonserial Dynamic Programming

## Approximate Dynamic Programming

*Solving the Curses of Dimensionality*

**Author**: Warren B. Powell

**Publisher:**John Wiley & Sons

**ISBN:**9780470182956

**Category:**Mathematics

**Page:**480

**View:**3111

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## Applied Dynamic Programming

**Author**: Richard E. Bellman,Stuart E Dreyfus

**Publisher:**Princeton University Press

**ISBN:**1400874653

**Category:**Computers

**Page:**390

**View:**3293

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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.

## Dynamic Programming

*Sequential Scientific Management*

**Author**: A. Kaufmann,R. Cruon

**Publisher:**Academic Press

**ISBN:**0080955444

**Category:**Computers

**Page:**277

**View:**9207

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This work discusses the value of dynamic programming as a method of optimization for the sequential phenomena encountered in economic studies or in advanced technological programs such as those associated with space flights. The dynamic programs which are considered are defined for a deterministic universe, or one with probabilities; both categories are of equal importance in the practice of operations research or of scientific management.

## Optimal Decisions

*Dynamic Programming, Loss Functions, Knapsack Problem, Subset Sum Problem, Earley Parser, Optimal Design, Longest Common Subsequenc*

**Author**: Source Wikipedia

**Publisher:**University-Press.org

**ISBN:**9781230596020

**Category:**

**Page:**76

**View:**2867

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 74. Chapters: Dynamic programming, Loss functions, Knapsack problem, Subset sum problem, Earley parser, Optimal design, Longest common subsequence problem, Expected utility hypothesis, Forward-backward algorithm, Secretary problem, Viterbi algorithm, Bellman equation, Floyd-Warshall algorithm, Smith-Waterman algorithm, Levenshtein distance, Mean squared error, Markov decision process, Matrix chain multiplication, Longest increasing subsequence, Approximate string matching, Word wrap, Response surface methodology, Backward induction, Partially observable Markov decision process, Needleman-Wunsch algorithm, Stopping time, Curse of dimensionality, Regret, Bayesian experimental design, Longest common substring problem, Odds algorithm, Hamilton-Jacobi-Bellman equation, Hirschberg's algorithm, Optimal stopping, Optimal substructure, Cost-utility analysis, Sum of absolute differences, Maximum subarray problem, Optimal decision, Huber loss function, Utility maximization problem, Viscosity solution, Mean squared prediction error, Expenditure minimization problem, Taguchi loss function, Sum of absolute transformed differences, Generalized expected utility, Bitonic tour, Shortest common supersequence, Disorder problem, Hunt-McIlroy algorithm, Overlapping subproblem, Weak axiom of cost minimization, 0-1 loss function.

## Dynamic Programming and the Calculus of Variations

**Author**: Dreyfus

**Publisher:**Academic Press

**ISBN:**0080955274

**Category:**Computers

**Page:**247

**View:**6347

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Dynamic Programming and the Calculus of Variations

## Dynamic Programming for Coding Interviews

*A Bottom-Up approach to problem solving*

**Author**: Meenakshi,Kamal Rawat

**Publisher:**Notion Press

**ISBN:**194655670X

**Category:**Computers

**Page:**142

**View:**2325

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I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function, int fib(int n){ return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2); } and waited for the result. I wait… and wait… and wait… With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term. More than 200 million times? Is it reporting function calls or scam of some government? The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory. A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc. The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.

## Dynamic Programming

*Applications to Agriculture and Natural Resources*

**Author**: John O.S. Kennedy

**Publisher:**Springer Science & Business Media

**ISBN:**9400941919

**Category:**Juvenile Nonfiction

**Page:**344

**View:**5920

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Humans interact with and are part of the mysterious processes of nature. Inevitably they have to discover how to manage the environment for their long-term survival and benefit. To do this successfully means learning something about the dynamics of natural processes, and then using the knowledge to work with the forces of nature for some desired outcome. These are intriguing and challenging tasks. This book describes a technique which has much to offer in attempting to achieve the latter task. A knowledge of dynamic programming is useful for anyone interested in the optimal management of agricultural and natural resources for two reasons. First, resource management problems are often problems of dynamic optimization. The dynamic programming approach offers insights into the economics of dynamic optimization which can be explained much more simply than can other approaches. Conditions for the optimal management of a resource can be derived using the logic of dynamic programming, taking as a starting point the usual economic definition of the value of a resource which is optimally managed through time. This is set out in Chapter I for a general resource problem with the minimum of mathematics. The results are related to the discrete maximum principle of control theory. In subsequent chapters dynamic programming arguments are used to derive optimality conditions for particular resources.

## Dynamic Programming in Economics

**Author**: Cuong Van,Rose-Anne Dana

**Publisher:**Springer Science & Business Media

**ISBN:**9781402074097

**Category:**Business & Economics

**Page:**201

**View:**8263

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Dynamic Programming in Economics is an outgrowth of a course intended for students in the first year PhD program and for researchers in Macroeconomics Dynamics. It can be used by students and researchers in Mathematics as well as in Economics. The purpose of Dynamic Programming in Economics is twofold: (a) to provide a rigorous, but not too complicated, treatment of optimal growth models in infinite discrete time horizon, (b) to train the reader to the use of optimal growth models and hence to help him to go further in his research. We are convinced that there is a place for a book which stays somewhere between the "minimum tool kit" and specialized monographs leading to the frontiers of research on optimal growth.

## Dynamic programming

*a practical introduction*

**Author**: David K. Smith

**Publisher:**Prentice Hall

**ISBN:**N.A

**Category:**Computers

**Page:**160

**View:**3411

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## Introduction to Dynamic Programming

*International Series in Modern Applied Mathematics and Computer Science*

**Author**: Leon Cooper,Mary W. Cooper

**Publisher:**Elsevier

**ISBN:**1483136620

**Category:**Mathematics

**Page:**300

**View:**946

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Introduction to Dynamic Programming introduces the reader to dynamic programming and presents the underlying mathematical ideas and results, as well as the application of these ideas to various problem areas. A large number of solved practical problems and computational examples are included to clarify the way dynamic programming is used to solve problems. A consistent notation is applied throughout the text for the expression of quantities such as state variables and decision variables. This monograph consists of 10 chapters and opens with an overview of dynamic programming as a particular approach to optimization, along with the basic components of any mathematical optimization model. The following chapters discuss the application of dynamic programming to variational problems; functional equations and the principle of optimality; reduction of state dimensionality and approximations; and stochastic processes and the calculus of variations. The final chapter looks at several actual applications of dynamic programming to practical problems, such as animal feedlot optimization and optimal scheduling of excess cash investment. This book should be suitable for self-study or for use as a text in a one-semester course on dynamic programming at the senior or first-year, graduate level for students of mathematics, statistics, operations research, economics, business, industrial engineering, or other engineering fields.