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Author: Warren B. Powell
Publisher: John Wiley & Sons
ISBN: 0470182954
Category : Mathematics
Languages : en
Pages : 487
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Book Description
A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.
Author: Warren B. Powell
Publisher: John Wiley & Sons
ISBN: 0470182954
Category : Mathematics
Languages : en
Pages : 487
Get Book Here
Book Description
A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.
Author: Craig A. Kluever
Publisher: John Wiley & Sons
ISBN: 1119723477
Category : Technology & Engineering
Languages : en
Pages : 480
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Book Description
The simulation of complex, integrated engineering systems is a core tool in industry which has been greatly enhanced by the MATLAB® and Simulink® software programs. The second edition of Dynamic Systems: Modeling, Simulation, and Control teaches engineering students how to leverage powerful simulation environments to analyze complex systems. Designed for introductory courses in dynamic systems and control, this textbook emphasizes practical applications through numerous case studies—derived from top-level engineering from the AMSE Journal of Dynamic Systems. Comprehensive yet concise chapters introduce fundamental concepts while demonstrating physical engineering applications. Aligning with current industry practice, the text covers essential topics such as analysis, design, and control of physical engineering systems, often composed of interacting mechanical, electrical, and fluid subsystem components. Major topics include mathematical modeling, system-response analysis, and feedback control systems. A wide variety of end-of-chapter problems—including conceptual problems, MATLAB® problems, and Engineering Application problems—help students understand and perform numerical simulations for integrated systems.
Author: Meenakshi
Publisher: Notion Press
ISBN: 194655670X
Category : Computers
Languages : en
Pages : 168
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Book Description
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.
Author: Roberto Osti
Publisher: The Monacelli Press, LLC
ISBN: 1580935516
Category : Art
Languages : en
Pages : 353
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Book Description
An essential visual guide for artists to the mastery and use of advanced human anatomy skills in the creation of figurative art. Dynamic Human Anatomy picks up where Basic Human Anatomy leaves off and offers artists and art students a deeper understanding of anatomy, including anatomy in motion, and how that essential skill is applied to the creation of fine figurative art.
Author: Lucian Busoniu
Publisher: CRC Press
ISBN: 1439821097
Category : Computers
Languages : en
Pages : 280
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Book Description
From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.
Author: Sanjoy Dasgupta
Publisher: McGraw-Hill Higher Education
ISBN: 0077388496
Category : Computer algorithms
Languages : en
Pages : 338
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Book Description
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text DasGupta also offers a Solutions Manual which is available on the Online Learning Center."Algorithms is an outstanding undergraduate text equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel it is a joy to read." Tim Roughgarden Stanford University
Author: Foster Morrison
Publisher: Courier Corporation
ISBN: 0486131718
Category : Mathematics
Languages : en
Pages : 418
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Book Description
This text illustrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. It describes the benefits and limitations of the available modeling tools, showing engineers and scientists how any system can be rendered simpler and more predictable. Written by a well-known authority in the field, this volume employs practical examples and analogies to make models more meaningful. The more universal methods appear in considerable detail, and advanced dynamic principles feature easy-to-understand examples. The text draws careful distinctions between mathematical abstractions and observable realities. Additional topics include the role of pure mathematics, the limitations of numerical methods, forecasting in the presence of chaos and randomness, and dynamics without calculus. Specialized techniques and case histories are coordinated with a carefully selected and annotated bibliography. The original edition was a Library of Science Main Selection in May, 1991. This new Dover edition features corrections by the author and a new Preface.
Author: Tavis Leaf Glover
Publisher: Tavis Leaf Glover
ISBN: 1733761225
Category : Art
Languages : en
Pages : 506
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Book Description
Serious visual artists can now easily understand and apply the secret geometry that masters used to create remarkable art. Superior mathematical skills aren’t required because there are hundreds of excellent step-by-step diagrams to explain everything with simplicity. Learn how the ancient and modern masters used dynamic symmetry to promote unity, movement, rhythm, and strength. These qualities, along with many others, allowed their art to have visual clarity, impact, and stand the test of time. This is an essential book for painters, photographers, sculptors, and cinematographers that hold composition and design with a high priority. For far too long, artists have been stuck with the basic tools of artistic composition, like the rule of thirds and leading lines. Unfortunately, we’re incapable of reaching the master level if all we know are the basics. Powerful tools like dynamic symmetry and other composition techniques have been kept a secret from all of us. It’s time to learn of them, push past any plateau that stands in our way, and finally unlock our true potential!
Author: John Scott
Publisher: Hachette UK
ISBN: 1856753816
Category : Health & Fitness
Languages : en
Pages : 455
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Book Description
John Scott's Ashtanga Yoga is a step-by-step illustrated guide that takes you through the balanced exercise routines and breathing techniques of this dynamic form. Carefully structured, this course starts with a simple sequence for beginners which, once mastered, provides the foundation for moving on to the next level. - Purify your body with dynamic movement and precise postures - Develop physical and mental strength, increased stamina and greater flexibility - Includes a foreword by Shri K Pattabhi Jois, founder of Ashtanga Yoga - This new edition has been fully revised and updated This essential guide is the perfect introduction to yoga or the ideal gift for those who want to take their yoga practice to the next level. Author John Scott studied with yogi Shri K Pattabhi Jois at the Ashtanga Yoga Research Institute in India, where he qualified to teach Ashtanga Yoga around the world. He has instructed many people in Ashtanga Yoga, including high-profile celebrities Madonna and Sting. John now spends much of his time teaching international workshops and undertaking teacher trainings.
Author: Ronald W. Morrison
Publisher: Springer Science & Business Media
ISBN: 3662065606
Category : Computers
Languages : en
Pages : 155
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Book Description
Details robustness, stability, and performance of Evolutionary Algorithms in dynamic environments
