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Regression Dynamic Programming For High Dimensional Continuous State Problems With Application To Stochastic Multiple Reservoir Optimization
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Author :Kit-Yee Daisy Fan Publisher :Ann Arbor, Mich. : University Microfilms International ISBN 13 : Total Pages :282 pages Book Rating :4.E/5 ( download)
Book Synopsis Regression Dynamic Programming for High-dimensional Continuous-state Problems with Application to Stochastic Multiple-reservoir Optimization by : Kit-Yee Daisy Fan
Download or read book Regression Dynamic Programming for High-dimensional Continuous-state Problems with Application to Stochastic Multiple-reservoir Optimization written by Kit-Yee Daisy Fan and published by Ann Arbor, Mich. : University Microfilms International. This book was released on 2002 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Programming Based Operation of Reservoirs by : K. D. W. Nandalal
Download or read book Dynamic Programming Based Operation of Reservoirs written by K. D. W. Nandalal and published by Cambridge University Press. This book was released on 2007-05-10 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming is a method of solving multi-stage problems in which decisions at one stage become the conditions governing the succeeding stages. It can be applied to the management of water reservoirs, allowing them to be operated more efficiently. This is one of the few books dedicated solely to dynamic programming techniques used in reservoir management. It presents the applicability of these techniques and their limits on the operational analysis of reservoir systems. The dynamic programming models presented in this book have been applied to reservoir systems all over the world, helping the reader to appreciate the applicability and limits of these models. The book also includes a model for the operation of a reservoir during an emergency situation. This volume will be a valuable reference to researchers in hydrology, water resources and engineering, as well as professionals in reservoir management.
Book Synopsis Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2006 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applying Experimental Design and Regression Splines to High-dimensional Continuous-state Stochastic Dynamic Programming by : Victoria Chung-Ping Chen
Download or read book Applying Experimental Design and Regression Splines to High-dimensional Continuous-state Stochastic Dynamic Programming written by Victoria Chung-Ping Chen and published by . This book was released on 1993 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Neural Approximations for Optimal Control and Decision by : Riccardo Zoppoli
Download or read book Neural Approximations for Optimal Control and Decision written by Riccardo Zoppoli and published by Springer Nature. This book was released on 2019-12-17 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :Institute for Operations Research and the Management Sciences. National Meeting Publisher : ISBN 13 : Total Pages :284 pages Book Rating :4.E/5 ( download)
Book Synopsis INFORMS Annual Meeting by : Institute for Operations Research and the Management Sciences. National Meeting
Download or read book INFORMS Annual Meeting written by Institute for Operations Research and the Management Sciences. National Meeting and published by . This book was released on 2004 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Institute for Operations Research and the Management Sciences. National Meeting Publisher : ISBN 13 : Total Pages :180 pages Book Rating :4.E/5 ( download)
Book Synopsis INFORMS Conference Program by : Institute for Operations Research and the Management Sciences. National Meeting
Download or read book INFORMS Conference Program written by Institute for Operations Research and the Management Sciences. National Meeting and published by . This book was released on 2000 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Naval Research Logistics written by and published by . This book was released on 2006 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Topics on System Analysis and Integrated Water Resources Management by : Andrea Castelletti
Download or read book Topics on System Analysis and Integrated Water Resources Management written by Andrea Castelletti and published by Elsevier. This book was released on 2006-10-19 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Integrated Water Resources Management (IWRM) paradigm has been worldwide recognized as the only feasible way currently available to ensure a sustainable perspective in planning and managing water resource systems. It is the inspiring principle of the Water Framework Directive, adopted by the European Union in 2000, as well as the main reference for all the water related activity of UNESCO in the third world countries. However, very often, real world attempts of implementing IWRM fail for the lack of a systematic approach and the inadequacy of tools and techniques adopted to address the intrinsically complex nature of water systems. This book explores recent and important contributions of System Analysis and Control Theory to the technical application of such paradigm and to the improvement of its theoretical basis. Its prior aim is to demonstrate how the modelling and computational difficulties posed by this paradigm might be significantly reduced by strengthening the efficiency of the solution techniques, instead of weakening the integration requirements. The first introductory chapter provides the reader with a logical map of the book, by formalizing the IWRM paradigm in a nine-step decisional procedure and by identifying the points where the contribution of System Analysis and Control Theory is more useful. The book is then organized in three sections whose chapters analyze some theoretical and mathematical aspects of these contributions or presents design applications. The outstanding research issues on the border between System Analysis and IWRM is depicted in the last chapter, where a pull of scientists and experts, coordinated by Prof. Tony Jakeman describe the foreseeable scenario. The book is based on the most outstanding contributions to the IFAC workshop on Modelling and Control for Participatory Planning and Managing Water Systems held in Venice, September 28- October 1, 2004. That workshop has been conceived and organized with the explicit purpose of producing this book: the maximum length of the papers was unusually long (of the size of a book chapter) and only five long oral presentations were planned each day, thus allowing for a very useful and constructive discussion. - Contributions from the leading world specialists of the field - Integration of technical modelling aspects and participatory decision-making - Good compromise between theory and application
Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton
Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Author :Center for Uncertain Systems: Tools for Optimization and Management Publisher : ISBN 13 : Total Pages :332 pages Book Rating :4.F/5 ( download)
Book Synopsis CUSTOM (Center for Uncertain Systems: Tools for Optimization and Management Conference) by : Center for Uncertain Systems: Tools for Optimization and Management
Download or read book CUSTOM (Center for Uncertain Systems: Tools for Optimization and Management Conference) written by Center for Uncertain Systems: Tools for Optimization and Management and published by . This book was released on 2004 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Dynamic Programming by : Richard E. Bellman
Download or read book Applied Dynamic Programming written by Richard E. Bellman and published by Princeton University Press. This book was released on 2015-12-08 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Reinforcement Learning and Stochastic Optimization by : Warren B. Powell
Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a “diary problem” that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1967 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Ant Colony Optimization by : Marco Dorigo
Download or read book Ant Colony Optimization written by Marco Dorigo and published by MIT Press. This book was released on 2004-06-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.
Book Synopsis Gaussian Processes for Machine Learning by : Carl Edward Rasmussen
Download or read book Gaussian Processes for Machine Learning written by Carl Edward Rasmussen and published by MIT Press. This book was released on 2005-11-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
Book Synopsis Differential Dynamic Programming by : David H. Jacobson
Download or read book Differential Dynamic Programming written by David H. Jacobson and published by Elsevier Publishing Company. This book was released on 1970 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
